{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# phonon calculation style\n",
    "\n",
    "**Lucas M. Hale**, [lucas.hale@nist.gov](mailto:lucas.hale@nist.gov?Subject=ipr-demo), *Materials Science and Engineering Division, NIST*.\n",
    "\n",
    "## Introduction\n",
    "\n",
    "The phonon calculation style applies small atomic displacements to a unit cell system and evaluates the forces on the atoms to evaluate phonon-based properties.\n",
    "\n",
    "### Version notes\n",
    "\n",
    "- 2019-07-30: Notebook added.\n",
    "- 2021-02-25: Quasiharmonic calculations added.\n",
    "\n",
    "### Additional dependencies\n",
    "\n",
    "- [spglib](https://atztogo.github.io/spglib/python-spglib.html)\n",
    "- [phonopy](https://atztogo.github.io/phonopy/)\n",
    "- [seekpath](https://pypi.org/project/seekpath/)\n",
    "\n",
    "### Disclaimers\n",
    "\n",
    "- [NIST disclaimers](http://www.nist.gov/public_affairs/disclaimer.cfm)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Method and Theory\n",
    "\n",
    "Starting with an initial system, [spglib](https://atztogo.github.io/spglib/python-spglib.html) is used to identify the associated primitive unit cell.  The primitive cell is passed to [phonopy](https://atztogo.github.io/phonopy/), which constructs super cell systems with small atomic displacements.  A LAMMPS calculation is performed on the displaced systems to evaluate the atomic forces on each atom without relaxing.  The measured atomic forces are then passed back to phonopy, which computes force constants for the system.  Quasiharmonic approximation calculations can also be performed, where the phonons are evaluated at multiple strains of the system and used to estimate additional thermodynamic data.\n",
    " \n",
    "See [phonopy](https://atztogo.github.io/phonopy/) documentation for more details about the package and the associated theory.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demonstration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.1. Library imports\n",
    "\n",
    "Import libraries needed by the calculation. The external libraries used are:\n",
    "\n",
    "- [numpy](http://www.numpy.org/)\n",
    "\n",
    "- [DataModelDict](https://github.com/usnistgov/DataModelDict)\n",
    "\n",
    "- [atomman](https://github.com/usnistgov/atomman)\n",
    "\n",
    "- [iprPy](https://github.com/usnistgov/iprPy)\n",
    "\n",
    "- [spglib](https://atztogo.github.io/spglib/python-spglib.html)\n",
    "\n",
    "- [phonopy](https://atztogo.github.io/phonopy/)\n",
    "\n",
    "- [seekpath](https://pypi.org/project/seekpath/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Notebook last executed on 2021-03-08 using iprPy version 0.10.4\n"
     ]
    }
   ],
   "source": [
    "# Standard library imports\n",
    "from pathlib import Path\n",
    "import os\n",
    "import sys\n",
    "import uuid\n",
    "import shutil\n",
    "import datetime\n",
    "from collections import OrderedDict\n",
    "from math import floor\n",
    "from copy import deepcopy\n",
    "\n",
    "# http://www.numpy.org/\n",
    "import numpy as np\n",
    "\n",
    "# https://matplotlib.org/\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# https://atztogo.github.io/spglib/python-spglib.html\n",
    "import spglib\n",
    "\n",
    "# https://atztogo.github.io/phonopy/phonopy-module.html\n",
    "import phonopy\n",
    "\n",
    "# https://github.com/usnistgov/DataModelDict \n",
    "from DataModelDict import DataModelDict as DM\n",
    "\n",
    "# https://github.com/usnistgov/atomman \n",
    "import atomman as am\n",
    "import atomman.lammps as lmp\n",
    "import atomman.unitconvert as uc\n",
    "\n",
    "# https://github.com/usnistgov/iprPy\n",
    "import iprPy\n",
    "\n",
    "from IPython.display import Image\n",
    "\n",
    "print('Notebook last executed on', datetime.date.today(), 'using iprPy version', iprPy.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2. Default calculation setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify calculation style\n",
    "calc_style = 'phonon'\n",
    "\n",
    "# If workingdir is already set, then do nothing (already in correct folder)\n",
    "try:\n",
    "    workingdir = workingdir\n",
    "\n",
    "# Change to workingdir if not already there\n",
    "except:\n",
    "    workingdir = Path('calculationfiles', calc_style)\n",
    "    if not workingdir.is_dir():\n",
    "        workingdir.mkdir(parents=True)\n",
    "    os.chdir(workingdir)\n",
    "    \n",
    "# Initialize connection to library\n",
    "library = iprPy.Library()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Assign values for the calculation's run parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.1. Specify system-specific paths\n",
    "\n",
    "- __lammps_command__ is the LAMMPS command to use (required).\n",
    "\n",
    "- __mpi_command__ MPI command for running LAMMPS in parallel. A value of None will run simulations serially."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "lammps_command = 'lmp_serial'\n",
    "mpi_command = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2. Load interatomic potential\n",
    "\n",
    "- __potential_name__ gives the name of the potential_LAMMPS reference record in the iprPy library to use for the calculation.  \n",
    "\n",
    "- __potential__ is an atomman.lammps.Potential object (required)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "potential_name = '1999--Mishin-Y--Ni--LAMMPS--ipr1'\n",
    "\n",
    "# Retrieve potential and parameter file(s)\n",
    "potential = library.get_lammps_potential(id=potential_name, getfiles=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3. Load initial unit cell system\n",
    "\n",
    "- __ucell__ is an atomman.System representing a fundamental unit cell of the system (required).  Here, this is loaded from the database for the prototype."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avect =  [ 3.520,  0.000,  0.000]\n",
      "bvect =  [ 0.000,  3.520,  0.000]\n",
      "cvect =  [ 0.000,  0.000,  3.520]\n",
      "origin = [ 0.000,  0.000,  0.000]\n",
      "natoms = 4\n",
      "natypes = 1\n",
      "symbols = ('Ni',)\n",
      "pbc = [ True  True  True]\n",
      "per-atom properties = ['atype', 'pos']\n",
      "     id |   atype |  pos[0] |  pos[1] |  pos[2]\n",
      "      0 |       1 |   0.000 |   0.000 |   0.000\n",
      "      1 |       1 |   0.000 |   1.760 |   1.760\n",
      "      2 |       1 |   1.760 |   0.000 |   1.760\n",
      "      3 |       1 |   1.760 |   1.760 |   0.000\n"
     ]
    }
   ],
   "source": [
    "# Create ucell by loading prototype record\n",
    "ucell = am.load('crystal', potential=potential, family='A1--Cu--fcc', database=library)\n",
    "\n",
    "print(ucell)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.4. Modify system\n",
    "\n",
    "- __sizemults__ list of three integers specifying how many times the ucell vectors of $a$, $b$ and $c$ are replicated in creating system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "sizemults = [3, 3, 3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.5. Specify calculation-specific run parameters\n",
    "\n",
    "- __displacementdistance__ is the displacement distance scalar to use when applying random displacements to the atoms to compute the force constants.   \n",
    "- __symmetryprecision__ is the absolute precision tolerance to use in determining crystal symmetry elements for identifying the primitive unit cell.   \n",
    "- __strainrange__ is the size of the largest strain used for the quasiharmonic calculations.\n",
    "- __numstrains__ is the number of strain states to use for the quasiharmonic calculation.  Needs to be odd and either 1 or greater than or equal to 5.  If set to 1, then the quasiharmonic calculations will not be performed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "displacementdistance = uc.set_in_units(0.01, 'angstrom')\n",
    "symmetryprecision = 1e-5\n",
    "strainrange = 0.01\n",
    "numstrains = 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Define calculation function(s) and generate template LAMMPS script(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.1. phonon.template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('phonon.template', 'w') as f:\n",
    "    f.write(\"\"\"# LAMMPS input script that evaluates atomic forces without relaxing\n",
    "\n",
    "box tilt large\n",
    "\n",
    "<atomman_system_pair_info>\n",
    "\n",
    "thermo_style custom step pe\n",
    "thermo_modify format float %.13e\n",
    "\n",
    "dump dumpy all custom 1 forces.dump id type x y z fx fy fz\n",
    "dump_modify dumpy format <dump_modify_format>\n",
    "\n",
    "run 0\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.2. phonon_quasiharmonic()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def phonon_quasiharmonic(lammps_command, ucell, potential, mpi_command=None, a_mult=3, b_mult=3, c_mult=3,\n",
    "           distance=0.01, symprec=1e-5, strainrange=0.01, numstrains=5):\n",
    "    \"\"\"\n",
    "    Function that performs phonon and quasiharmonic approximation calculations\n",
    "    using phonopy and LAMMPS.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    lammps_command :str\n",
    "        Command for running LAMMPS.\n",
    "    ucell : atomman.System\n",
    "        The unit cell system to perform the calculation on.\n",
    "    potential : atomman.lammps.Potential\n",
    "        The LAMMPS implemented potential to use.\n",
    "    mpi_command : str, optional\n",
    "        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS\n",
    "        will run serially.\n",
    "    a_mult : int, optional\n",
    "        The a size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    b_mult : int, optional\n",
    "        The b size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    c_mult : int, optional\n",
    "        The c size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    distance : float, optional\n",
    "        The atomic displacement distance used for computing the phonons.\n",
    "        Default value is 0.01.\n",
    "    symprec : float, optional\n",
    "        Absolute length tolerance to use in identifying symmetry of atomic\n",
    "        sites and system boundaries. Default value is 1e-5.\n",
    "    strainrange : float, optional\n",
    "        The range of strains to apply to the unit cell to use with the\n",
    "        quasiharmonic calculations.  Default value is 0.01.\n",
    "    numstrains : int, optional\n",
    "        The number of strains to use for the quasiharmonic calculations.\n",
    "        Must be an odd integer.  If 1, then the quasiharmonic calculations\n",
    "        will not be performed.  Default value is 5.\n",
    "    \"\"\"\n",
    "    # Build filedict if function was called from iprPy\n",
    "    try:\n",
    "        assert __name__ == pkg_name\n",
    "        calc = iprPy.load_calculation(calculation_style)\n",
    "        filedict = calc.filedict\n",
    "    except:\n",
    "        filedict = {}\n",
    "\n",
    "    # Get lammps units\n",
    "    lammps_units = lmp.style.unit(potential.units)\n",
    "    \n",
    "    # Get lammps version date\n",
    "    lammps_date = lmp.checkversion(lammps_command)['date']\n",
    "    \n",
    "    # Get original box vectors\n",
    "    vects = ucell.box.vects\n",
    "\n",
    "    # Generate the range of strains\n",
    "    if numstrains == 1:\n",
    "        zerostrain = phononcalc(lammps_command, ucell, potential,\n",
    "                                mpi_command=mpi_command,\n",
    "                                a_mult=a_mult, b_mult=b_mult, c_mult=c_mult,\n",
    "                                distance=distance, symprec=symprec,\n",
    "                                lammps_date=lammps_date)\n",
    "        phonons = [zerostrain['phonon']]\n",
    "        qha = None\n",
    "\n",
    "    elif numstrains % 2 == 0 or numstrains < 5:\n",
    "        raise ValueError('Invalid number of strains: must be odd and 1 or >= 5')\n",
    "    else:\n",
    "        strains = np.linspace(-strainrange, strainrange, numstrains)\n",
    "        istrains = np.linspace(-(numstrains-1)/2, (numstrains-1)/2, numstrains, dtype=int)\n",
    "\n",
    "        volumes = []\n",
    "        energies = []\n",
    "        phonons = []\n",
    "        temperatures = None\n",
    "        free_energy = None\n",
    "        heat_capacity = None\n",
    "        entropy = None\n",
    "\n",
    "        # Loop over all strains\n",
    "        for istrain, strain in zip(istrains, strains):\n",
    "\n",
    "            # Identify the zero strain run\n",
    "            if istrain == 0:\n",
    "                zerostrainrun = True\n",
    "                savefile = 'phonopy_params.yaml'\n",
    "            else:\n",
    "                zerostrainrun = False\n",
    "                savefile = f'phonopy_params_{istrain}.yaml'\n",
    "            \n",
    "            # Generate system at the strain\n",
    "            newvects = vects * (1 + strain)\n",
    "            ucell.box_set(vects=newvects, scale=True)\n",
    "            volumes.append(ucell.box.volume)\n",
    "            system = ucell.supersize(a_mult, b_mult, c_mult)\n",
    "\n",
    "            # Define lammps variables\n",
    "            lammps_variables = {}\n",
    "            system_info = system.dump('atom_data', f='disp.dat',\n",
    "                                    potential=potential,\n",
    "                                    return_pair_info=True)\n",
    "            lammps_variables['atomman_system_pair_info'] = system_info\n",
    "\n",
    "            # Set dump_modify_format based on lammps_date\n",
    "            if lammps_date < datetime.date(2016, 8, 3):\n",
    "                lammps_variables['dump_modify_format'] = '\"%d %d %.13e %.13e %.13e %.13e %.13e %.13e\"'\n",
    "            else:\n",
    "                lammps_variables['dump_modify_format'] = 'float %.13e'\n",
    "\n",
    "            # Write lammps input script\n",
    "            template_file = 'phonon.template'\n",
    "            lammps_script = 'phonon.in'\n",
    "            template = iprPy.tools.read_calc_file(template_file, filedict)\n",
    "            with open(lammps_script, 'w') as f:\n",
    "                f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))\n",
    "\n",
    "            # Run LAMMPS\n",
    "            output = lmp.run(lammps_command, 'phonon.in', mpi_command=mpi_command)\n",
    "\n",
    "            # Extract system energy\n",
    "            thermo = output.simulations[0]['thermo']\n",
    "            energy = uc.set_in_units(thermo.PotEng.values[-1], lammps_units['energy'])\n",
    "\n",
    "            # Scale energy by sizemults and append to list\n",
    "            energies.append(energy / (a_mult * b_mult * c_mult))\n",
    "\n",
    "            # Compute phonon info for ucell\n",
    "            phononinfo = phononcalc(lammps_command, ucell, potential, mpi_command=mpi_command,\n",
    "                                    a_mult=a_mult, b_mult=b_mult, c_mult=c_mult,\n",
    "                                    distance=distance, symprec=symprec, savefile=savefile,\n",
    "                                    plot=zerostrainrun, lammps_date=lammps_date)\n",
    "            phonons.append(phononinfo['phonon'])\n",
    "            \n",
    "            # Extract temperature values from the first run\n",
    "            if temperatures is None:\n",
    "                temperatures = phononinfo['thermal_properties']['temperatures']\n",
    "                \n",
    "                # Initialize QHA input arrays\n",
    "                free_energy = np.empty((len(temperatures), len(strains)))\n",
    "                heat_capacity = np.empty((len(temperatures), len(strains)))\n",
    "                entropy = np.empty((len(temperatures), len(strains)))\n",
    "            \n",
    "            # Get values for zerostrainrun\n",
    "            if zerostrainrun is True:\n",
    "                zerostrain = phononinfo\n",
    "            \n",
    "            # Copy values to qha input arrays\n",
    "            free_energy[:, istrain] = phononinfo['thermal_properties']['free_energy']\n",
    "            entropy[:, istrain] = phononinfo['thermal_properties']['entropy']\n",
    "            heat_capacity[:, istrain] = phononinfo['thermal_properties']['heat_capacity']\n",
    "        \n",
    "        # Compute qha\n",
    "        try:\n",
    "            qha = phonopy.PhonopyQHA(volumes=volumes,\n",
    "                        electronic_energies=energies,\n",
    "                        temperatures=temperatures,\n",
    "                        free_energy=free_energy,\n",
    "                        cv=heat_capacity,\n",
    "                        entropy=entropy)\n",
    "        except:\n",
    "            qha = None\n",
    "    \n",
    "    results = {}    \n",
    "    \n",
    "    # Add phonopy objects\n",
    "    results['phonon_objects'] = phonons\n",
    "    results['qha_object'] = qha\n",
    "    \n",
    "    # Extract zerostrain properties\n",
    "    results['band_structure'] = zerostrain['band_structure']\n",
    "    results['density_of_states'] = zerostrain['dos']\n",
    "\n",
    "    # Convert units on thermal properties\n",
    "    results['thermal_properties'] = zerostrain['thermal_properties']\n",
    "    results['thermal_properties']['temperature'] = results['thermal_properties'].pop('temperatures')\n",
    "    results['thermal_properties']['Helmholtz'] = uc.set_in_units(results['thermal_properties'].pop('free_energy'), 'kJ/mol')\n",
    "    results['thermal_properties']['entropy'] = uc.set_in_units(results['thermal_properties'].pop('entropy'), 'J/K/mol')\n",
    "    results['thermal_properties']['heat_capacity_v'] = uc.set_in_units(results['thermal_properties'].pop('heat_capacity'), 'J/K/mol')\n",
    "    \n",
    "    if qha is not None:\n",
    "\n",
    "        # Create QHA plots\n",
    "        qha.plot_bulk_modulus()\n",
    "        plt.xlabel('Volume ($Å^3$)', size='large')\n",
    "        plt.ylabel('Energy ($eV$)', size='large')\n",
    "        plt.savefig('bulk_modulus.png', dpi=400, bbox_inches='tight')\n",
    "        plt.close()\n",
    "\n",
    "        qha.plot_helmholtz_volume()\n",
    "        plt.savefig('helmholtz_volume.png', dpi=400)\n",
    "        plt.close()\n",
    "\n",
    "        # Package volume vs energy scans\n",
    "        results['volume_scan'] = {}\n",
    "        results['volume_scan']['volume'] = np.array(volumes)\n",
    "        results['volume_scan']['strain'] = strains\n",
    "        results['volume_scan']['energy'] = np.array(energies)\n",
    "        \n",
    "        # Compute and add QHA properties\n",
    "        properties = qha.get_bulk_modulus_parameters()\n",
    "        results['E0'] = uc.set_in_units(properties[0], 'eV')\n",
    "        results['B0'] = uc.set_in_units(properties[1], 'eV/angstrom^3')\n",
    "        results['B0prime'] = uc.set_in_units(properties[2], 'eV/angstrom^3')\n",
    "        results['V0'] = uc.set_in_units(properties[3], 'angstrom^3')\n",
    "        \n",
    "        results['thermal_properties']['volume'] = uc.set_in_units(np.hstack([qha.get_volume_temperature(), np.nan]), 'angstrom^3')\n",
    "        results['thermal_properties']['thermal_expansion'] = np.hstack([qha.get_thermal_expansion(), np.nan])\n",
    "        results['thermal_properties']['Gibbs'] = uc.set_in_units(np.hstack([qha.get_gibbs_temperature(), np.nan]), 'eV')\n",
    "        results['thermal_properties']['bulk_modulus'] = uc.set_in_units(np.hstack([qha.get_bulk_modulus_temperature(), np.nan]), 'GPa')\n",
    "        results['thermal_properties']['heat_capacity_p_numerical'] = uc.set_in_units(np.hstack([qha.get_heat_capacity_P_numerical(), np.nan]), 'J/K/mol')\n",
    "        results['thermal_properties']['heat_capacity_p_polyfit'] = uc.set_in_units(np.hstack([qha.get_heat_capacity_P_polyfit(), np.nan]), 'J/K/mol')\n",
    "        results['thermal_properties']['gruneisen'] = np.hstack([qha.get_gruneisen_temperature(), np.nan])\n",
    "    \n",
    "    return results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3. phononcalc()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def phononcalc(lammps_command, ucell, potential, mpi_command=None,\n",
    "               a_mult=3, b_mult=3, c_mult=3, distance=0.01, symprec=1e-5, \n",
    "               savefile='phonopy_params.yaml', plot=True, lammps_date=None):\n",
    "    \"\"\"\n",
    "    Uses phonopy to compute the phonons for a unit cell structure using a\n",
    "    LAMMPS interatomic potential.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    lammps_command :str\n",
    "        Command for running LAMMPS.\n",
    "    ucell : atomman.System\n",
    "        The unit cell system to perform the calculation on.\n",
    "    potential : atomman.lammps.Potential\n",
    "        The LAMMPS implemented potential to use.\n",
    "    mpi_command : str, optional\n",
    "        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS\n",
    "        will run serially.\n",
    "    a_mult : int, optional\n",
    "        The a size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    b_mult : int, optional\n",
    "        The b size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    c_mult : int, optional\n",
    "        The c size multiplier to use on ucell before running the phonon\n",
    "        calculation.  Must be an int and not a tuple.  Default value is 3.\n",
    "    distance : float, optional\n",
    "        The atomic displacement distance used for computing the phonons.\n",
    "        Default value is 0.01.\n",
    "    symprec : float, optional\n",
    "        Absolute length tolerance to use in identifying symmetry of atomic\n",
    "        sites and system boundaries. Default value is 1e-5.\n",
    "    savefile: str, optional\n",
    "        The name of the phonopy yaml backup file.  Default value is\n",
    "        'phonopy_params.yaml'.\n",
    "    plot : bool, optional\n",
    "        Flag indicating if band structure and DOS figures are to be generated.\n",
    "        Default value is True.\n",
    "    lammps_date : datetime.date, optional\n",
    "        The version date associated with lammps_command.  If not given, the\n",
    "        version will be identified.\n",
    "    \"\"\"\n",
    "    # Build filedict if function was called from iprPy\n",
    "    try:\n",
    "        assert __name__ == pkg_name\n",
    "        calc = iprPy.load_calculation(calculation_style)\n",
    "        filedict = calc.filedict\n",
    "    except:\n",
    "        filedict = {}\n",
    "\n",
    "    # Get lammps units\n",
    "    lammps_units = lmp.style.unit(potential.units)\n",
    "    \n",
    "    # Get lammps version date\n",
    "    if lammps_date is None:\n",
    "        lammps_date = lmp.checkversion(lammps_command)['date']\n",
    "    \n",
    "    # Use spglib to find primitive unit cell of ucell\n",
    "    convcell = ucell.dump('spglib_cell')\n",
    "    primcell = spglib.find_primitive(convcell, symprec=symprec)\n",
    "    primucell = am.load('spglib_cell', primcell, symbols=ucell.symbols).normalize()\n",
    "    \n",
    "    # Initialize Phonopy object\n",
    "    phonon = phonopy.Phonopy(primucell.dump('phonopy_Atoms', symbols=potential.elements(primucell.symbols)),\n",
    "                             [[a_mult, 0, 0], [0, b_mult, 0], [0, 0, c_mult]],\n",
    "                             factor=phonopy.units.VaspToTHz)\n",
    "    phonon.generate_displacements(distance=distance)\n",
    "    \n",
    "    # Loop over displaced supercells to compute forces\n",
    "    forcearrays = []\n",
    "    for supercell in phonon.supercells_with_displacements:\n",
    "        \n",
    "        # Save to LAMMPS data file\n",
    "        system = am.load('phonopy_Atoms', supercell, symbols=primucell.symbols)\n",
    "        system_info = system.dump('atom_data', f='disp.dat',\n",
    "                                  potential=potential,\n",
    "                                  return_pair_info=True)\n",
    "        \n",
    "        # Define lammps variables\n",
    "        lammps_variables = {}\n",
    "        lammps_variables['atomman_system_pair_info'] = system_info\n",
    "\n",
    "        # Set dump_modify_format based on lammps_date\n",
    "        if lammps_date < datetime.date(2016, 8, 3):\n",
    "            lammps_variables['dump_modify_format'] = '\"%d %d %.13e %.13e %.13e %.13e %.13e %.13e\"'\n",
    "        else:\n",
    "            lammps_variables['dump_modify_format'] = 'float %.13e'\n",
    "\n",
    "        # Write lammps input script\n",
    "        template_file = 'phonon.template'\n",
    "        lammps_script = 'phonon.in'\n",
    "        template = iprPy.tools.read_calc_file(template_file, filedict)\n",
    "        with open(lammps_script, 'w') as f:\n",
    "            f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))\n",
    "        \n",
    "        # Run LAMMPS\n",
    "        lmp.run(lammps_command, 'phonon.in', mpi_command=mpi_command)\n",
    "        \n",
    "        # Extract forces from dump file\n",
    "        forcestructure = am.load('atom_dump', 'forces.dump')\n",
    "        forces = uc.set_in_units(forcestructure.atoms.force, lammps_units['force'])\n",
    "        forcearrays.append(forces)\n",
    "    \n",
    "    results = {}\n",
    "\n",
    "    # Set computed forces\n",
    "    phonon.set_forces(forcearrays)\n",
    "    \n",
    "    # Save to yaml file    \n",
    "    phonon.save(savefile)\n",
    "    \n",
    "    # Compute band structure    \n",
    "    phonon.produce_force_constants()\n",
    "    phonon.auto_band_structure(plot=plot)\n",
    "    results['band_structure'] = phonon.get_band_structure_dict()\n",
    "    if plot:\n",
    "        plt.ylabel('Frequency (THz)')\n",
    "        plt.savefig(Path('.', 'band.png'), dpi=400)\n",
    "        plt.close()\n",
    "    \n",
    "    # Compute density of states\n",
    "    phonon.auto_total_dos(plot=False)\n",
    "    phonon.auto_projected_dos(plot=False)\n",
    "    dos = phonon.get_total_dos_dict()\n",
    "    dos['frequency'] = uc.set_in_units(dos.pop('frequency_points'), 'THz')\n",
    "    dos['projected_dos'] = phonon.get_projected_dos_dict()['projected_dos']\n",
    "    results['dos'] = dos\n",
    "    \n",
    "    # Compute thermal properties\n",
    "    phonon.run_thermal_properties()\n",
    "    results['thermal_properties'] = phonon.get_thermal_properties_dict()\n",
    "    \n",
    "    results['phonon'] = phonon\n",
    "    return results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Run calculation function(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_dict = phonon_quasiharmonic(lammps_command, ucell, potential,\n",
    "                                    mpi_command = mpi_command,\n",
    "                                    a_mult = sizemults[0],\n",
    "                                    b_mult = sizemults[1],\n",
    "                                    c_mult = sizemults[2],\n",
    "                                    distance = displacementdistance,\n",
    "                                    symprec = symmetryprecision,\n",
    "                                    strainrange = strainrange,\n",
    "                                    numstrains = numstrains)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['phonon_objects', 'qha_object', 'band_structure', 'density_of_states', 'thermal_properties', 'volume_scan', 'E0', 'B0', 'B0prime', 'V0'])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_dict.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Report results\n",
    "\n",
    "The calculation both returns results_dict containing phonon information and generates files. \n",
    "\n",
    "#### 5.1. Phonon properties\n",
    "\n",
    "In results_dict:\n",
    "\n",
    "- __phonon_objects__ is a list containing all of the Phonopy objects at all of the strains evaluated.\n",
    "- __band_structure__ contains the evaluated band structure points for the zero strain structure.\n",
    "- __density_of_states__ contains the evaluated density of states (both total and projected) for the zero strain structure.\n",
    "- __thermal_properties__ contains the temperature-dependent Helmholtz free energy, entropy, and constant volume heat capacity.\n",
    "\n",
    "Generated files:\n",
    "\n",
    "- __band.png__ plots the band structure for the zero strain structure.\n",
    "- __phonopy_params.yaml__ is the YAML-formatted Phonopy data that can be read back in to generate a Phonopy object later.  \n",
    "\n",
    "#### 5.2. Quasiharmonic properties\n",
    "\n",
    "These are only generated if numstrains is greater than 1.\n",
    "\n",
    "In results_dict:\n",
    "\n",
    "- __qha_object__ is the PhonopyQHA object.\n",
    "- __volume_scan__ contains the energy versus volume evaluations taken from the different strain states.\n",
    "- __E0, B0, B0prime, V0__ are the energy, Bulk modulus, B' modulus, and volume associated with the interpolated equilibrium state from the volume scan.\n",
    "- __thermal_properties__ is expanded to also include the temperature-dependent volume, thermal expansion, Gibbs free energy, bulk modulus, constant pressure heat capacity, and Grüneisen parameter.\n",
    "\n",
    "Generated files:\n",
    "\n",
    "- __bulk_modulus.png__ plots the volume scan data as it is used to estimate the bulk modulus.  This plot provides a quick visual means of telling if the quasiharmonic analysis is likely good for the strains explored. \n",
    "- __helmholtz.png__ plots the helmholtz free energy versus volume.  \n",
    "- __phonopy_params_\\*.yaml__ are the YAML-formatted Phonopy data for the non-zero strains that can be read back in to generate Phonopy objects later. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Band structure plot and values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "keys of \"band_structure\": dict_keys(['qpoints', 'distances', 'frequencies', 'eigenvectors', 'group_velocities'])\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('keys of \"band_structure\":', results_dict['band_structure'].keys())\n",
    "Image(\"band.png\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Volume versus energy scan plot and values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "keys of \"volume_scan\": dict_keys(['volume', 'strain', 'energy'])\n",
      "E0 = -17.800064782202853 eV\n",
      "B0 = 187.3449504939102 GPa\n",
      "B0`= 163.88079256518492 GPa\n",
      "V0 = 43.61305033417225 Å^3\n"
     ]
    },
    {
     "data": {
      "image/png": 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v76wMaKrp6Og46QhlYGBgFtoU6+rqyu7du9PR0XF0fDMwMFB4+s3Y2Fj6+vrS29ubJNm5c+e0hjDt7e3ZvXv30d+j7u7ujIyMnDRbqVTS19d39Nc3bNiQjRs3TvlZ0BJOOy1Zvbo4c/Bgsm1bOX0AAAAAAIC555ZbqmfWr08WLmx8F2hCbRMTExOzXQKmo7e397jrmI5ceZQky5YtOy5bdPXUnj17jp6eMl1tbW3HfVzPUceRwcjo6Gg6OjoyNDQ0o1NaGtn1iE2bNh13utCRAdGRP4/x8fHs2rXruJNnbrzxxuP+7Gp55pGxVVdXVwYGBo6OgB5++OEMDw+nUqnU5fdwNn3nO9/JxRdffNznHnrooVx00UWz1Ig5Z+/epLMzKfrr/vWvT/bs8Q9iAAAAAADgeJVKcs45yTPPnDrzO7+T/OxnyQlfq4WpaIWvhxreQA1GR0czODiY8fHx9PT0ZMeOHbNd6ZTK7Do6OpodO3Zk165dGR8fT6VSSXt7e5YtW5aurq709vbmiiuumNHg5liVSiV33313duzYkfHx8YyPjx99Xk9PTwYGBqZ8jVWzaoW/aGgC731v8rWvFWe+8pXJHAAAAAAAwBF/9VfJf/tvxZk1a5ItW8rpQ8tpha+HGt4ANLFW+IuGJnDvvckHP1icueyy5L77yukDAAAAAAA0v8OHk/POS37yk+Lc976XvO1t5XSi5bTC10MXzHYBAKDB3ve+5LWvLc585SvJT39aTh8AAAAAAKD5fe1r1Uc3f/RHRjfMe4Y3ANDqFi5M1q4tzkxMOAYSAAAAAAD4D5/8ZPXMDTc0vgc0OcMbAJgP1qyZHOAU2bo1OXCgnD4AAAAAAEDz+tGPkgceKM6cfXbyoQ+V0weamOENAMwHZ5+dXH55cWbfvuTLXy6nDwAAAAAA0Lw+9anqmeuvT047rfFdoMkZ3gDAfHH99dUzmzc3vgcAAAAAANC8KpXkjjuKM6edlgwMlNMHmpzhDQDMF3/6p8mb3lSc+frXkx//uJw+AAAAAABA89m2LXnmmeLMRz+avPKV5fSBJmd4AwDzxYIFU1ufDw01vgsAAAAAANB8Dh1Kbr65eu4v/qLxXWCOMLwBgPnkuuuS008vztx+e/Lss2W0AQAAAAAAmsn99yd79xZn/vAPk+7ucvrAHGB4AwDzyVlnJVdcUZz59a+Tz3++nD4AAAAAAEDz+OQnq2c+/vHG94A5xPAGAOab66+vnvn0pxvfAwAAAAAAaB7/8A/J179enDn33ORDHyqnD8wRhjcAMN9ceGHyB39QnHn44ckfAAAAAADA/PCpT1XPrF+fLF7c+C4whxjeAMB809Y2tVNvbrml8V0AAAAAAIDZt39/8pnPFGdOPz1Zu7acPjCHGN4AwHx09dXJy15WnLnrruTJJ8vpAwAAAAAAzJ6tW5Nnny3OXH118vKXl9MH5hDDGwCYj172suTaa4szzz+fbNtWTh8AAAAAAGB2HDw4tVPwP/7xxneBOcjwBgDmq/Xrq2duvTU5dKjxXQAAAAAAgNlx773Jv/xLceZd70rOP7+cPjDHGN4A8P+zd/fRfdeFvcDfoYXKg5JWUSaiNBk+bQxNYArb3VQSn47ziQYUBQWhkYdCpZCCu2f33u3sQsJDW0qhDQIyD4o0yjZRnI26i1Mu1yYgON1F+iu66YZK+RVBHkvuH73NWmi/vzTJ75un1+ucnpO07/x+b9pTIMn79/kwU73udclb31qc2bgx+frXy+kDAAAAAACU74oramecdgO7ZHgDADPZmWfWzozkeEkAAAAAAGDqufvu5H/9r+LMK1+ZvPe95fSBKcjwBgBmsve9LznooOLM17+ebNhQTh8AAAAAAKA8K1fWzpx5ZjJ7dv27wBRleAMAM9ns2UlnZ3FmaChZvbqcPgAAAAAAQDl+/evkxhuLM3vvnZx6ajl9YIoyvAGAme6002ov1a+7Lnn88XL6AAAAAAAA9XfNNcmTTxZnTjwxmTevnD4wRRneAMBMd+CBybHHFmc2bUpuuqmcPgAAAAAAQH09/XSyalXt3KJF9e8CU5zhDQCw9X7WWlat2nrtFAAAAAAAMLXdckvy858XZ972tuT3f7+cPjCFGd4AAMkf/3Fy2GHFmYGB5PvfL6cPAAAAAABQP1dcUTtz9tn17wHTgOENAJA0NIz81BsAAAAAAGDqGhhIvvvd4sz8+cl73lNOH5jiDG8AgK0+8pHkRS8qznzxi8mvf11OHwAAAAAAYPyN5LSbs85KZs2qfxeYBgxvAICt9tsv+fjHizNPPplce20pdQAAAAAAgHH24IPJTTcVZ/bZJznllHL6wDRgeAMA/KfTT6+dufrqZMuW+ncBAAAAAADGV29v8tRTxZmPfSxpbCynD0wDhjcAwH967WuTY44pzvz0p8ltt5XTBwAAAAAAGB9PPbX1xbW1LFpU/y4wjRjeAAA7OvPM2plVq+rfAwAAAAAAGD99fcm//3tx5u1vT173unL6wDRheAMA7OjP/iw5+ODizNe/ntx/fzl9AAAAAACAsbviitqZs8+ufw+YZgxvAIAdzZ6ddHbWzo3kOEoAAAAAAGDi3Xnn1h9FmpuTd72rnD4wjRjeAADPd+qpyZ57Fmeuuy757W/L6QMAAAAAAIzeypW1M4sWJXuYEMDu8rcGAHi+l70sWbCgOFOtJl/4Qjl9AAAAAACA0fn3f09uvrk4s99+ycknl9MHphnDGwBg5848s3Zm1apkaKj+XQAAAAAAgNFZvTp5+unizMknJy96UTl9YJoxvAEAdu7oo5PDDy/O3HVX7TthAQAAAACAifHkk1uHN7WcdVb9u8A0ZXgDAOxcQ8PIT70BAAAAAAAmn5tvTn75y+LMu96VvPrV5fSBacjwBgDYtRNOSPbfvzgzkv9pBwAAAAAAyjU0lKxYUTt3zjn17wLTmOENALBr++6bfPzjxZmnnkquvbaUOgAAAAAAwAjdcUcyMFCcec1rkvb2cvrANGV4AwAUO+OM2pnVq5MtW+rfBQAAAAAAGJmRnHazaFGyh9kAjIW/QQBAsVe/uvba/Wc/S7761XL6AAAAAAAAxX72s+RLXyrOvOhFyUknldMHpjHDGwCgtjPPrJ1Ztar+PQAAAAAAgNquvLL2SfWnnJK88IXl9IFpzPAGAKjtPe9JXvnK4sw3vpHcd185fQAAAAAAgJ179NHkmmuKMw0NyVlnldMHpjnDGwCgtlmzks7O2rmrr65/FwAAAAAAYNduuCGpVosz731v0txcTh+Y5gxvAICROfXUZK+9ijPXX5889lg5fQAAAAAAgB09+2yyYkXt3OLF9e8CM4ThDQAwMi99adLRUZzZvDn5whfK6QMAAAAAAOzoa19LfvKT4swb3pD86Z+W0wdmAMMbAGDkzjyzdmbVqmRoqP5dAAAAAACAHS1bVjuzeHHS0FD/LjBDGN4AACP35jcnb3xjcebuu5M77iinDwAAAAAAsNU99yTf+lZx5mUvSz70oXL6wAxheAMAjFxDw8hPvQEAAAAAAMqzfHntzJlnJnPm1L8LzCCGNwDA7vnwh5PGxuLM2rXJgw+W0wcAAAAAAGa6X/4yufHG4sycOUlnZzl9YAYxvAEAds8++yQnn1ycefrp5JpryukDAAAAAAAz3dVXJ089VZz56EeTl760nD4wgxjeAAC77/TTa2euvnrrAAcAAAAAAKifJ55Irrqqdu6cc+rfBWYgwxsAYPcdemjyjncUZ37xi+SWW8rpAwAAAAAAM9VNN229aqpIW1ty2GHl9IEZxvAGABidM8+snbniivr3AAAAAACAmWpoKFm2rHbuU5+qfxeYoQxvAIDRefe7k6am4sx3v5vcdVc5fQAAAAAAYKb5x39M7rmnOPOa1yTvfGcpdWAmMrwBAEZn1qyRnXqzcmX9uwAAAAAAwEw0ktNuzjkn2cM0AOrF3y4AYPROOSXZZ5/izOc/n/zqV+X0AQAAAACAmeInP0luvbU4M3ductJJ5fSBGcrwBgAYvcbG2v/D/uSTyWc+U04fAAAAAACYKa64IhkaKs4sXJjsu285fWCGMrwBAMbmrLNqZ666Knnmmfp3AQAAAACAmaBaTa6/vjgza9bIvoYPjInhDQAwNr/3e8nb3lac+bd/S/72b8vpAwAAAAAA091nPpM89lhxpqMjecUryukDM5jhDQAwdmefXTuzcmX9ewAAAAAAwHT3zDMj+5r7pz5V/y6A4Q0AMA7e857kkEOKM7ffnvzgB6XUAQAAAACAaeuWW5Kf/aw4c9RRyR/+YTl9YIYzvAEAxm7WrOSMM2rnnHoDAAAAAABjs2xZ7YzTbqA0hjcAwPj4xCeSvfcuztx4Y/LQQ+X0AQAAAACA6ebOO5M77ijOvPKVyQc+UE4fwPAGABgn8+YlH/1oceaJJ5Jrry2nDwAAAAAATDfLl9fOLFqUzJ5d/y5AEsMbAGA8LVpUO7NqVfLMM/XvAgAAAAAA08m//muydm1xZt99k1NPLacPkMTwBgAYT4cdlrzlLcWZn/0s+cpXSqkDAAAAAADTxqpVyZYtxZmTT04aG8vpAyQxvAEAxttITr1ZubL+PQAAAAAAYLp47LGkt7c409CQnHNOOX2AYYY3AMD4eu97k4MPLs58+9vJvfeW0wcAAAAAAKa6G25IHn64OPNnf5b87u+W0wcYZngDAIyv2bOTM86onbvyyvp3AQAAAACAqe7ZZ5MVK2rnFi+ufxfgeQxvAIDxd+qpyQteUJz53Odqr/MBAAAAAGCmu+225L77ijOHH5685S2l1AF2ZHgDAIy/l7wkOeGE4szjjyfXXltOHwAAAAAAmKqWL6+dWbw4aWiofxfgeQxvAID6WLSodmbVqmTLlvp3AQAAAACAqejee5P+/uLMy16WfPjD5fQBnsfwBgCojze8Ifkv/6U488ADyVe/WkodAAAAAACYckZy2s0ZZyRz5tS/C7BThjcAQP2M5NSbK66ofw8AAAAAAJhqfvnL5MYbizNz5iSf/GQ5fYCdMrwBAOrn/e9PDjqoOPPNbyY/+lE5fQAAAAAAYKpYvTp58snizEc+krz0peX0AXbK8AYAqJ8999x6xGUtV15Z/y4AAAAAADBVPPlkctVVtXOLF9e/C1DI8AYAqK/TTqt9t+wNNyTVajl9AAAAAABgsrvppuTBB4szxxyTHHZYOX2AXTK8AQDq64ADkg99qDjz298m119fTh8AAAAAAJjMhoaSyy+vnfvUp+rfBajJ8AYAqL9Fi2pnrrwy2bKl/l0AAAAAAGAy6+9P7rmnOPPqVyfvelc5fYBChjcAQP21tiZHH12cqVSS224rpw8AAAAAAExWl11WO3POOckevt0Pk4G/iQBAOUZy6s3KlfXvAQAAAAAAk9UPf5j8wz8UZ+bOTU46qZw+QE2GNwBAOY49Nnn5y4sz3/hG8i//Uk4fAAAAAACYbC6/vHbmk59M9tuv/l2AETG8AQDKseeeWz8ZqOXKK+vfBQAAAAAAJpv/+I/kxhuLM3vumZx1Vjl9gBExvAEAyrNwYbLXXsWZG25IHnmknD4AAAAAADBZXHll8tRTxZkTTqh9ujxQKsMbAKA8L3tZcvzxxZlHH00++9lS6gAAAAAAwKTw2GPJ1VfXzp17bv27ALvF8AYAKNeiRbUzK1cmzz5b/y4AAAAAADAZ3HBDsmlTcaa9PfmDPyinDzBihjcAQLmOPDJ505uKM/ffn/zDP5TTBwAAAAAAJtKWLcmyZbVz551X/y7AbjO8AQDKN9JTbwAAAAAAYLr7yle2viC1yGGHbT3xBph0DG8AgPJ1dCQHHlicue225L77yukDAAAAAAAT5dJLa2fOPTdpaKh/F2C3Gd4AAOXba6+ks7N2zqk3AAAAAABMZ3femXz3u8WZAw9MPvzhcvoAu83wBgCYGJ2dyezZxZnrr0+q1XL6AAAAAABA2S67rHZm0aJkzpz6dwFGxfAGAJgYv/M7yXHHFWceeyy59tpy+gAAAAAAQJk2bky+9KXizD77JJ/8ZDl9gFExvAEAJs4559TOrFyZPPNM/bsAAAAAAECZVqxInn22OHPyycm8eeX0AUbF8AYAmDh/+IfJUUcVZ3760+Tv/q6cPgAAAAAAUIZqtfaJ7w0NyeLF5fQBRs3wBgCYWCP5pGH58vr3AAAAAACAsvT2Jo8+Wpx5//uT3/3dcvoAo2Z4AwBMrA9+MDn44OLMP/1Tsn59OX0AAAAAAKCennoqueKK2rklS+rfBRgzwxsAYGLNnp2cdVbt3IoV9e8CAAAAAAD1dvPNyc9/Xpx505uSo48upw8wJoY3AMDEO/XUZJ99ijNf/GLyi1+U0wcAAAAAAOphaCi57LLaufPOSxoa6t8HGDPDGwBg4s2bl3zsY8WZp59Orr66nD4AAAAAAFAP3/52cvfdxZn585MPfKCcPsCYGd4AAJPD2WfXzqxenTz+eP27AAAAAABAPVx6ae3M4sXJrFn17wKMC8MbAGByeO1rk3e9qzjz618nn/98OX0AAAAAAGA8/ehHyW23FWcaG5NTTimnDzAuDG8AgMlj8eLameXLt96BCwAAAAAAU8nll9fOdHYm++1X/y7AuDG8AQAmj/b25HWvK8788IfJt75VTh8AAAAAABgPDz6YfO5zxZnZs5NFi8rpA4wbwxsAYPJoaEjOOad2bsWK+ncBAAAAAIDxsmpV8tRTxZkPfzg56KBy+gDjxvAGAJhcTjwxmTu3OHPrrclPflJOHwAAAAAAGIvf/ja56qrauSVL6t8FGHeGNwDA5LLPPlvvsC0yNJSsXFlOHwAAAAAAGIu/+ZvkoYeKM8cckxx+eDl9gHFleAMATD5nnpnMmlWcue66pFotpw8AAAAAAIzGs88my5bVzjntBqYswxsAYPJ5xSuSjo7izGOPbR3fAAAAAADAZHXrrcl99xVnXv/65J3vLKcPMO4MbwCAyWnx4tqZK65Innmm/l0AAAAAAGA0LrusdmbJkqShof5dgLowvAEAJqc3vSl585uLMz/9afL3f19OHwAAAAAA2B3f/35y++3FmZe9LPnIyIiowQAAIABJREFUR8rpA9SF4Q0AMHmN5NSb5cvr3wMAAAAAAHbXSE67OeusZM6c+ncB6sbwBgCYvD74weQVryjOfOc7ycBAOX0AAAAAAGAkfvrTpK+vOLP33snpp5fTB6gbwxsAYPLac8+ta/9aVqyofxcAAAAAABipFSuSLVuKMx//ePLiF5dSB6gfwxsAYHI77bStq/8iN92U/Pu/l9MHAAAAAACKbN6cfOYzxZmGhuRTnyqnD1BXhjcAwOQ2b17ysY8VZ55+Orn66nL6AAAAAABAkWuuSX7zm+LMe9+bHHpoOX2AujK8AQAmv7PPrp25+urkiSfq3wUAAAAAAHblqaeS5ctr55YsqX8XoBSGNwDA5Pe61yXvfGdx5te/Tj7/+XL6AAAAAADAznzhC8nPf16cOfLI5I//uJw+QN0Z3gAAU8PixbUzy5cnQ0P17wIAAAAAAM/17LPJJZfUzi1ZkjQ01L8PUArDGwBganj727eefFPk3nuTb3+7nD4AAAAAALC9225L/vmfizPz5yfHHltOH6AUhjcAwNTQ0JCcc07t3IoV9e8CAAAAAADP1dNTO3Puucns2fXvApTG8AYAmDpOPDGZO7c485WvJPffX04fAAAAAABIkjvvTG6/vTjz4hcnJ59cTh+gNIY3AMDUsc8+ycKFxZmhoWTlynL6AAAAAABAklxySe3MWWcl++5b/y5AqQxvAICp5cwzk1mzijPXXZds3lxOHwAAAAAAZraf/CT58peLMy94wdavbwPTjuENADC1HHxwsmBBcebRR7eObwAAAAAAoN4uv3zraexFTjklOeCAcvoApTK8AQCmnsWLa2euuCLZsqX+XQAAAAAAmLkefDC5/vrizB57JOeeW04foHSGNwDA1PPmNydvelNx5oEHkr//+1LqAAAAAAAwQ115ZfLkk8WZBQuS5uZy+gClM7wBAKamkZx6s3x5/XsAAAAAADAzPfposmpV7dz559e/CzBhDG8AgKnp2GOTgw4qztx+ezIwUE4fAAAAAABmluuuSx5+uDjz1rcmRxxRTh9gQhjeAABT0557JmedVTt3+eX17wIAAAAAwMzy9NPJZZfVznV11b8LMKEMbwCAqeu005K99y7OfPGLyb/+azl9AAAAAACYGdauTX72s+LMYYcl73hHOX2ACWN4AwBMXS9+cXLSScWZLVuSlSvL6QMAAAAAwPQ3NJRccknt3PnnJw0N9e8DTCjDGwBgalu8uHamtzf5zW/q3wUAAAAAgOmvvz+5++7izMEHJx/6UDl9gAlleAMATG2vfW3ynvcUZzZvTq67rpw+AAAAAABMbz09tTOLFyd77ln/LsCEM7wBAKa+JUtqZ5YvT555pv5dAAAAAACYvu66a+uJN0X23z857bRy+gATzvAGAJj6/vRPkze+sTjzwAPJLbeUUgcAAAAAgGnqkktqZ844I3nhC+vfBZgUDG8AgKmvoWFkp95cfnn9uwAAAAAAMD098EBy883Fmb32Ss4+u5Q6wORgeAMATA/HHZccdFBx5n//7+R73yunDwAAAAAA08uyZcmWLcWZk05KDjywnD7ApGB4AwBMD3vuObJXEVx2Wf27AAAAAAAwvTz0UPKZzxRnGhqS884rpw8waRjeAADTx8KFyX77FWduuSXZsKGcPgAAAAAATA9XXZX89rfFmfe9L3nNa8rpA0wahjcAwPTR2Jh84hPFmaGhZMWKcvoAAAAAADD1Pf54snJl7dz559e/CzDpGN4AANPLOecke9T4X5zrrksefricPgAAAAAATG033JD86lfFmT/6o+Too8vpA0wqhjcAwPQyf37ywQ8WZx57LOntLacPAAAAAABT15YtyaWX1s51ddW/CzApGd4AANPPkiW1M1dckTz1VP27AAAAAAAwdd1yS7JhQ3Hmta9N3vOecvoAk47hDQAw/bz5zclRRxVnfvGL5ItfLKcPAAAAAABTz9BQ0tNTO3feeckevvUOM5W//QDA9DSSU28uv3zrJ04AAAAAAPBct9+efP/7xZkDD0w++tFy+gCTkuENADA9vf/9SVNTcebuu5Nvf7ucPgAAAAAATC0jOe1m8eJkzpz6dwEmLcMbAGB6mjVr6yc8tVx2Wf27AAAAAAAwtfzwh8nXvlac2W+/pLOznD7ApGV4AwBMXyefnDQ2Fme+9rXkxz8upw8AAAAAAFPDpZfWznR21v4aNDDtGd4AANPXSF9tsGxZ/bsAAAAAADA1/Nu/JTfeWJyZPXtkp64D057hDQAwvS1atPUToCJ/8zfJL39ZTh8AAAAAACa35cuTZ54pzpxwQvKKV5TTB5jUDG8AgOntoIOSD32oOPPkk8nVV5fTBwAAAACAyataTXp7a+fOO6/+XYApwfAGAJj+liypnVm1Knn88fp3AQAAAABg8lq9OvnNb4oz7353cthh5fQBJj3DGwBg+nvDG5K3va0486tf1b6zFwAAAACA6evxx5Nly2rnurrq3wWYMgxvAICZ4dxza2cuvzx59tn6dwEAAAAAYPL57GeTX/6yOHPkkcmf/EkpdYCpwfAGAJgZ3vWu5LWvLc78+MfJ179eTh8AAAAAACaPZ55JLrmkdu7885OGhvr3AaYMwxsAYGbYY4+Rn3oDAAAAAMDMcvPNycaNxZlDD00++MFy+gBThuENADBzfPSjyQEHFGe++c3k7rvL6QMAAAAAwMQbGkouvrh2rqsrmTWr/n2AKcXwBgCYOfbeOznjjNo5p94AAAAAAMwcX/tacu+9xZmXvzw58cRy+gBTiuENADCznHFGMmdOceYLX0h+/vNy+gAAAAAAMLFGctrNuefW/toyMCMZ3gAAM8tLX1r7VQnPPJNceWU5fQAAAAAAmDj/9E9bfxSZOzdZuLCcPsCUY3gDAMw8555bO7N6dfLoo/XvAgAAAADAxBnJaTdnnZW88IX17wJMSYY3AMDM87rXJe9+d3GmWk0++9lS6gAAAAAAMAHuuSf56leLM3vvnZx9djl9gCnJ8AYAmJmWLKmdWbYs2bKl/l0AAAAAAChfd3ftzGmnJS95Sf27AFOW4Q0AMDO99a3J4YcXZyqV5O/+rpw+AAAAAACUp1JJbrqpODN79shexAnMaIY3AMDM1NAwsk+YLrus/l0AAAAAACjXpZcmzz5bnPnIR5JXvrKcPsCUZXgDAMxcxx+fvPzlxZnvfS+5445y+gAAAAAAUH8PPphcd13tXFdX/bsAU57hDQAwc+21V7JoUe3cJZfUvwsAAAAAAOVYvjx58snizPvfn7z+9eX0AaY0wxsAYGbr7Ez23bc487d/m9x3Xzl9AAAAAACon82bk6uuqp274IL6dwGmBcMbAGBmmzs3OeWU4szQUHLZZeX0AQAAAACgflavTh55pDjz1rcmb3pTOX2AKc/wBgDg3HOTWbOKMzfcsPXeXwAAAAAApqbHH0+WLaudc9oNsBsMbwAADjkk6egozjz5ZLJyZSl1AAAAAACog5G8wPKNb0za28vpA0wLhjcAAEly/vm1M6tWJY8+Wv8uAAAAAACMr2eeSXp6aucuvDBpaKh/H2DaMLwBAEiSlpbkmGOKM9Vq8pnPlNMHAAAAAIDxs3ZtsnFjcebQQ5MPfrCcPsC0YXgDALBNV1ftzLJlydNP178LAAAAAADjY2goufji2rmurmTWrPr3AaYVwxsAgG3a25PDDy/O/Oxnyc03l9MHAAAAAICxu+225J57ijMvf3ly4onl9AGmFcMbAIBtGhqS88+vnbvkkq2vkAAAAAAAYPIbyWk3556bzJlT/y7AtGN4AwCwveOOSw4+uDjzgx8k69aV0wcAAAAAgNH77neT73ynONPYmCxcWE4fYNoxvAEA2N6ee259ZUMtl1xS/y4AAAAAAIzNSE67Oeus5IUvrH8XYFoyvAEAeK5TT936Coci/f3J4GA5fQAAAAAA2H333pvcemtxZu+9k7PPLqcPMC0Z3gAAPNd++yVnnFE759QbAAAAAIDJq7u7dubUU5MDDqh/F2DaMrwBANiZRYuSvfYqzqxdm2zcWE4fAAAAAABGbuPG5KabijOzZydLlpTTB5i2DG8AAHbmwAOTj32sOLNlS7JsWTl9AAAAAAAYuUsv3fo13CInnJC86lXl9AGmLcMbAIBdWbIkaWgozlx7bfLQQ+X0AQAAAACgtgcfTK67rnZu6dL6dwGmPcMbAIBdec1rkve9rzjz298mV11VTh8AAAAAAGpbsSJ54onizPvel7z+9eX0AaY1wxsAgCJdXbUzK1cmjz9e/y4AAAAAABTbvDlZtap27oIL6t8FmBEMbwAAihx1VPJHf1Sc+dWvkhtuKKcPAAAAAAC7tnp18sgjxZm3vCV585tLqQNMf4Y3AAC1jOTUm8suS7ZsqX8XAAAAAAB27oknkmXLauecdgOMI8MbAIBa3vOe5LWvLc7cf3/yt39bTh8AAAAAAJ7v+uuTBx8szrzxjcnb315OH2BGMLwBAKhljz2S886rnevpSYaG6t8HAAAAAIAdPf100t1dO3fBBUlDQ/37ADOG4Q0AwEh89KPJgQcWZ/7P/0m+851y+gAAAAAA8J9uvDH56U+LM7/7u8mxx5bTB5gxDG8AAEZizpzknHNq53p66t8FAAAAAID/tGVLctFFtXNdXcmsWfXvA8wohjcAACP1yU8m++1XnPnqV5N//udy+gAAAAAAkHzpS8l99xVnDjooOemkcvoAM4rhDQDASDU2JgsX1s5demn9uwAAAAAAkAwNJX/917Vz55+/9WRzgHFmeAMAsDsWL05mzy7O3Hhj8vOfl9MHAAAAAGAmu/XW5J57ijMHHJCcdlo5fYAZx/AGAGB3HHxw8uEPF2eefjpZsaKcPgAAAAAAM9VIT7s599xkn33q3weYkQxvAAB213nn1c6sXp1s3lz/LgAAAAAAM9W3vpXceWdxprExOeOMcvoAM5LhDQDA7vqDP0je+c7izG9+k/T2ltMHAAAAAGAmGslpN4sWJS96Uf27ADOW4Q0AwGicf37tzPLlyVNP1b8LAAAAAMBM873vJd/+dnFm332Tc84ppw8wYxneAACMxlvfmrS2Fmd+8Yvk858vpw8AAAAAwEwyktNuTj89efGL698FmNEMb6BAtVpNa2tr+vr6JrpKTVOpK8C00NAwslNvLrkkefbZ+vcBAAAAAJgp7ror+drXijNz5iTnnltOH2BGM7xhWurs7MzcuXNTrVbH9Djr16/P4OBgOjo6snTp0vT396dSqYz5cethMnStVqvp6elJe3t7mpub09DQkIaGhjQ3N6ejoyO9vb1jevxKpZLOzs5RjYsqlUqWLl065g4AOzj22GT+/OLMj36U3HZbOX0AAAAAAGaC//k/a2c+8Ynkd36n/l2AGc/whmmlv78/zc3N6e3tTbVaTaVSGdPjDQ4ODr+9/aBk7ty5w6OS0fxorXU1yRTsunTp0sydOzdLly5NkrS1taW7uzvd3d1pa2vL4OBgOjs709DQMJzZXf39/ent7U1HR0caGhqGxzyDg4M7/Flv+7Pv6+vL0qVL09zcnObm5vT09KSpqWlUzw2wU7Nnj+wVE93d9e8CAAAAADAT/PjHyZe+VJyZPTvp6iqnDzDjzZ7oAjBWlUola9asSV9f35iHNs+1YcOGcX28bdra2sb9MSeqa6VSSXt7ezZt2pSurq5ceOGFaWxs3Gm2t7c3S5cuTU9PT/r6+jIwMLDL7Ej09fXt1uk320ZAAOPq5JOT//7fk4ce2nXmO99J7rgjOeqo0moBAAAAAExLF12UDA0VZ048MXnVq8rpA8x4TrxhSqlWq2lvb9/hKqNtJ5k0NjaOacSxM+vXrx/Xx0uSpqamdNfh5IOJ6FqtVodPxNm4cWO6u7sL/wwWLlyYjRs3pq2tLZVKJfPnzy/tKqw1a9aky7IZqId9903OPLN27qKL6t8FAAAAAGA6q1SSz3++OLPHHskFF5TTByCGN0xB/f39wyOTbdcZDQwMZGBgIPPmzRvX5xrvE3SSZO3ateP+mMnEdO3o6Ei1Ws26detGPHpqbGzMunXr0tTUlGq1mo6OjvGouktNTU0ZGBjIwoUL6/o8wAx31lnJC15QnPnKV5If/rCcPgAAAAAA01F3d7JlS3HmuOOSV7+6nD4AcdUUU0xjY2OGah0dN06q1Wqq1WoaGxuzcOHCNDc3Z968eaM6VWfbVVjd3d1paWmZFl37+/vT39+frq6uNDU1jep52tvb09/fn0qlMqrHKNLS0pILL7wwCxYsGNfHBdipAw5ITjklueqq4lx3d/K5z5XTCQAAAABgOvn5z5PPfrZ27tOfrnsVgO0Z3sAubDtBpru7e0ynpVQqlfT19aWlpaVuVx1NRNdtV1C1t7eP6rna2trS2NiYarWaNWvW7Nb1W9tOzBkcHEylUslDDz2UJHnxi1+cpqam4ccGKNV55yVr1hS/2uILX0j+6q+SQw4prRYAAAAAwLRw6aXJU08VZ9773uSww8rpA/D/Gd7ALmy7zuq4444b0+NsG6bU64qpZGK69vf3j+m5kuSII44YPvFmdzU1NY37KTkAYzJ/fvKhDyU33rjrzJYtWz85vPLK8noBAAAAAEx1v/rV1hc+1vLnf17/LgDPscdEF4DJamBgIE1NTWM6OWXp0qWpVCpZs2ZNXUciZXetVqvDbw8ODo76OXf2eABT2gUX1M5ce23yy1/WvwsAAAAAwHSxbFny+OPFmfb25A//sJw+ANsxvIFdqFQqaWlpGfXH9/f3p6enJwsWLBjT9U8jUXbXTZs2Db990UUXjfp5t510M5buAJPK7/9+8md/Vpx54olkxYpy+gAAAAAATHXVarJqVe2c026ACWJ4A7vQ0tKS448/flQfW61W09HRkcbGxlxzzTXj3Oz5yu66/Yk41Wp1+Iqq3X3ebcObI488crc/HmDSGsmpN6tWJY88Uv8uAAAAAABT3ZVX1v566h/9UfInf1JOH4DnmD3RBWCy6u7uHvXHnnbaaalWq1m3bt2Yrn8aqYno2tTUNDyc6e/vT2tra9auXTviK7WWLl06/DgLFizY/eJTxB133DGmj7/33nvHqQlQmqOP3voJ3u237zqzeXOyenXS1VVeLwAAAACAqebRR5Ply2vn/ut/TRoa6t8HYCcMb2Cc9fb2pq+vL11dXWlra5voOoXG0nXBggXp6ekZfn9wcDDNzc3p7u5OV41vJFcqlfT29iZJ1qxZs/vFp5Cjjz56oisAE+GCC4qHN8nWO4nPPjt5wQvK6QQAAAAAMNWsWZM89FBxprU1ecc7yukDsBOumoJxVKlU0tnZmaampjGdQlOGsXa98MILd/rzS5cuTWtr6/BpODt73tbW1iQZ93FSpVJJpVJJtVodt8cEGJV3vjN5wxuKM//xH8kNN5TTBwAAAABgqnniieTSS2vnPv1pp90AE8rwBsZRZ2dnkqlxistYuzY2Nmbt2rU7/bVtp99su05qm0qlkvb29lSr1XR3d4/LOKmnpyetra1paGhIc3NzmpubM3fu3MydOzednZ0ZHBwc83MA7LaGhq2n3tTS05M880z9+wAAAAAATDXXX7/1BYxFXv/65P3vL6cPwC4Y3sA46e/vT39/f9ra2ib9FVPj1XXBggWF10r19PSkubk5g4ODw29v2rQpa9eurXkdVS19fX2ZO3du1qxZk87OzmzYsCFDQ0N5+OGHs27duhxxxBHp7e1Na2vr8MgIoFTHHps0NxdnKpWkr6+cPgAAAAAAU8XTTycjeQH3pz+d7OFb3sDEahgaGhqa6BIwXpqbm3e44mhgYCAtLS2lPneZzzla4921v78/HR0dNa94Wrhw4ZhOA+rt7U1nZ2daWloyODiYNWvWZOHChbvM9/T0DJ+609TUlIGBgTQ2No76+UfjjjvuGNPH33vvvc8bDn3ve9/LUUcdNabHBUrS25v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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('keys of \"volume_scan\":',results_dict['volume_scan'].keys())\n",
    "print('E0 =', uc.get_in_units(results_dict['E0'], 'eV'), 'eV')\n",
    "print('B0 =', uc.get_in_units(results_dict['B0'], 'GPa'), 'GPa')\n",
    "print('B0`=', uc.get_in_units(results_dict['B0prime'], 'GPa'), 'GPa')\n",
    "print('V0 =', uc.get_in_units(results_dict['V0'], 'Å^3'), 'Å^3')\n",
    "\n",
    "Image(\"bulk_modulus.png\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Helmholtz free energy versus volume plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/CGABAAAAiD+hxg9KdMACAAAAgCQzODh9VODU4+5uM60+2TAqEAAAIDkQwAIAAAAQf0IFsBwO8040AAAAACChuN3+4SrvunbN7uqsl5ZmulUFGhNYWsqoQAAAgGRBAAsAAABA/Ak1gjA/n1kLAAAAABCHPB7p5s3AowIvXDD3JZusLP8RgYwKBAAASC0EsAAAAADEn1AdsBg/CAAAAAC28XhMt6pgIav+frsrtF6wUYFOp3TPPYwKBAAASHUEsAAAAADEn1AdsIqKYlMHAAAAAKSoiQmpu9s/XOUdHXj7tt0VWm/NGmnDhunLG7JautTu6gAAABDPCGABAAAAiD+hOmARwAIAAACAeRsfl7q6pPPnzZoatHK5pOFhuyu0VlqaGQk4M2S1YYNUUiItXmx3hQAAAEhUBLAAAAAAxB9GEAIAAACAJSYm/ENW3mOXSxoZsbtCay1caDpWzexitWGDtH69lJFhd4UAAABIRgSwAAAAAMQXj4cRhAAAAAAwBxMT0uXLvmDV1LBVe3vydbJatMgXqvJeeldxsQlhAQAAALHEP0EBAAAAxJe+vtCfDtABCwAAAECKmZgwzYJndrE6f96ErO7etbtCa2VnBx4VuGGD+U5OWprdFQIAAAA+BLAAAAAAxJdQ3a8kOmABAAAASErehsAzu1h5L+/csbtCay1bJm3cGDhklZ8vORx2VwgAAACEhwAWAAAAgPhy5UroxxDAAgAAAJCgPB7p2rXAnawuXJBu37a7QmutWuUfrvKODczLI2QFAACA5EAACwAAAEB8CRXAcjikgoLY1AIAAAAAEfB4pBs3gneyGhy0u0JrFRX5h6u8x8uW2V0dAAAAEH0EsAAAAADEl1AjCPPzpYX8KgMAAADAXh6P9OGH/l2svCGrgQG7K7SOwyGtXTs9XOVdTqeUnW13hQAAAIC9+NQCAAAAQHwJ1QGrsDA2dQAAAABIeR6PdPNm4E5W589L/f12V2idtDRp/XoTqtq4cXrIqqREysy0u0IAAAAgfhHAAgAAABBfQgWwiopiUwcAAACAlHHzZvBOVm633dVZJy3NdLLauNG3vIGrkhIpI8PuCgEAAIDERAALAAAAQHwJNYKQABYAAACACPT1Be5idf68uS9ZeMcFeoNVUxedrAAAAIDoIIAFAAAAIL4wghAAAABAhAYGfKGqc+d8lxcumC5XyaS42L+L1caNktMpLVpkd3UAAABAaiGABQAAACB+eDx0wAIAAAAwq+Fhqb3dF66aGrQK9etEolm92r+L1YYNUmmptHix3dUBAAAA8CKABQAAACB+9PWZT1NmQwALAAAASHrj49LFi9PDVd7jixeliQm7K7ROUVHgcYGlpVJWlt3VAQAAAAgHASwASDFnzkjHjkmXL0uDg1JOjvkm3Z490pYtdlcHAEh5ocYPSowgBAAAAJKEtwHuzC5W585JLpc0MmJ3hda5557A4wI3bJCys+2uDgAAAMB8EcBC3GtsbFRTU5NcLpdcLpdyc3OVl5enyspK7d+/X+Xl5XaXKElqbm7WK6+8ora2NvX29srtdis3N1dOp1MVFRXavXu3KioqIt7f5XKprq5Ou3fvVmVl5Zyf29DQoNLSUlVXV0dcAxLXyIh05Ih0+LB0/HjgxzzzjLR9u3TwoPTkk1JGRmxrBABAUnjzQuiABQAAACSU3l5fsGpq0Or8eWloyO7qrJOfH3hc4IYN0pIldlcHAAAAIJoIYCFu1dbWqr6+XpJUXl6u2tpaOZ1Oud1unTx5UvX19aqvr5fT6VRTU5NtQazGxkbV1tbK7XZLkpxO52SdLpdLbW1tamtrm6y1trY2ohBUa2urGhsb1djYKEmqrKzU7t279eCDD04GvSTJ7Xart7dXbW1tOnnypJqbm+VyuSRJLS0tFr1qJJLTp6V9+6SzZ0M/9vhxszZvlpqapLKy6NcHAMA0oTpgORxSQUFsagEAAAAQtsFB6cKFwN2senvtrs46q1b5d7HyXl+61O7qAAAAANiFABbijtvt1q5du9TW1qbc3Fy9+eabfuGqyspK1dXVqaamRo2Njdq6dasaGhpi3t2pqqpKzc3NcjqdeuGFF/w6U7nd7smAlmQ6UdXU1KipqUlNTU3Kzc2N+NzNzc1qbm4O+/F1dXXz6sCFxPTWW9LevdLAwNyed/astG2bdPSotHNndGoDACCgUB2w8vOlhfwaAwAAANhheNiMBpwarvIehzNNPFGsWOEfrvJezuMtXQAAAABJjE8uEHe2bt062bHp1KlTk52dAmloaJBkulDV1NRIUsxCWLt371Zra6uqq6sn65gpNzdXhw4dUnV19bTX1draqq1bt+rUqVPzCmGFy45wGux3+nRk4Suv/n7pscekEyfohAUAiKFQn9owfhAAAACIqvFx6dIl/y5W589LnZ3SxITdFVpj+fLA4wI3bjT3AQAAAMBcEMBCXKmqqpoMKdXV1c0avvJqaGhQa2vrZHepBx98MOrjCGtra0OGr6bKzc3VqVOntHzKb+4ul0u7du3SqVOnolan3eMZYZ+RETN2MNLwlVd/v1RVZcJcGRnW1AYAwKxCBbAKC2NTBwAAAJDEPB7p2jX/kNW5c1J7u3lvKRksXSpt2uQftNq4UcrLs7s6AAAAAMmEABbiRltb2+RIPW/nqHDV1tZOdsA6cOBAVENNbrdb9fX1cjqdYYWvvHJzc9XQ0DBZp2Rec319/ZxeazjKy8v17LPP+o1EROo4csSMEbTC2bPS669L+/dbsx8AALMKNYKQDlgAAABA2Pr6/EcFeo8HB+2uzhqLFpnOVZs2+cJW3uNVqySHw+4KAQAAAKQCAliIGwcOHJg83rdv35yeu2/fvslgkzfIFa3wUW1trSTNKXzlVV1dPS2A5d1vLgGslpYWOZ1OtbW1yeVy6ebNm5KkFStWyOl0qqKiIiZjDRHfDh+2fj8CWACAmKADFgAAADAnQ0PShQuBg1b//NZhwluwQHI6p4ervMdr1khpaXZXCAAAACDVEcBCXHC5XGpra5u8vnXr1jk9Pzc3V+Xl5ZN7NDQ0RC2A9eqrr0oywakHH3xQtbW1YY1K9KqsrJzs9OU118CY0+mc0zmRWn7zG+n4cWv3fPtt6cwZacsWa/cFAGAajyd0AIsOWAAAAEhBIyOSy+XfxercOenyZburs05xsX8Xq40bpZISKT3d7uoAAAAAIDgCWIgLM7tJVVRUzHkPb1coSWptbZXb7ba8E5Tb7Zbb7ZZkOm21tbWpsbFRfX19YZ8rUHCqpaWFcYGwzBtvRGffP/sz6fvflxYvjs7+AACor898sjQbAlgAAABIUuPjUldX4JBVR4c0MWF3hdZYtSrwuMDSUikry+7qAAAAACAyBLAQF2Z2hMrLy5vzHjODTa+++qqqq6vnVddMLpcr4O2NjY1hjxEsLS0Ne18gEtH61uORI9L69dLTT0sHD0rLl0fnPACAFBaq+5XECEIAAAAkNI9Hun7df1Tg+fNmjODwsN0VWmPJksAhq40bJYu/MwsAAAAAcYEAFmzndrv9AkiRdK5asWLFtOunTp2aV12BWNFRK1AHrN7e3nnvC3gNDkZv7xs3pP/8n6XnnpOqq6V//+9Na3gAACxx9Wrox9ABCwAAAAnA7fbvYuU9HhiwuzprZGZKGzYEDlrl50sOh90VAgAAAEDsEMCC7d57771p1yMNOc0MNrW2tkZc02zncDqdfoGxuYwP9I4wTBU///nP5/X8999/36JKUkdOTvTPMTQk/dVfSX/zN9LnPy/9h/8gbdkS/fMCAJJcqA5YDodUUBCbWgAAAIAQbt82XasCBa16euyuzhoLFkglJf5drDZtMl/KS0uzu0IAAAAAiA8EsGC7tra2adcjGT8o+Qe3ojXW79SpU6qqqlJra6ucTqcaGhoCdrUKJlBdc3l+onn44YftLiHlrF4du3ONjUl/+7dm7dkj/emfShUVfMMRABChUAGs/HxpIb/CAAAAIHZGR6WOjsAhq+5uu6uzzpo1gccFlpRIGRl2VwcAAAAA8Y9PL2C79vb2adcj7YAVKLjlcrksDzfl5uaqpaUl4uefPHnS77bdu3fPpyRJvmBXXl6eJaMSkbj27JGeeSb25z12zKz77jNBrM9+ljfoAABzFGoEIeMHAQAAEAUTE1JXl/+owHPnTPhqfNzuCq2xcmXgcYEbNkhZWXZXBwAAAACJjQAWbNfb2xu1veNx3F+g0YgVFRUR7VVfX69XXnnFr4tYbm6u9u3bp5qaGpWXl0e0NxLXli3S9u3S8eP2nP/0aekLX5CefVb68pelmhopwsZ2AIBUE6oDVmFhbOoAAABA0vF4pBs3/LtYnT9vxgjevWt3hdZYsiTwuMCNG6Xly+2uDgAAAACSFwEs2C6aISmXyxVXAaTm5ma/11tZWTnnLl3Nzc06cOCA8vLyVFtbq4qKCjmdTrndbr333nuqq6tTY2OjGhsbVV1drYaGBitfBhLAwYP2BbC8rl6VvvpV6etfl556Snr6afOGHwAAQYUKYNEBCwAAACG43SZUNTVk5Q1a9ffbXZ01MjNN16pAQauCAsnhsLtCAAAAAEg9BLBgO6s6YCXC2L1AQai6uro57VFbW6u2tjY1NDSourp62n25ubmqqKhQRUWF6uvrVVtbq8bGRrW2turUqVO2/IzefffdeT3//fffV01NjUXVpI4nn5Q2b5bOnp3/XhkZ0shI5M+/fVv6H//DrN/7PekrX5E+9SneDAQABMAIQgAAAIThzh3TtSpQN6sbN+yuzhppaVJJif+4wI0bpeJiacECuysEAAAAAExFAAu2m9kRKs/CWWXRHG84V21tbX7jBxsaGubc/aqtrU2nTp0K2dnr0KFDOnnypJqbm+VyubR161a1t7fPue75+uQnPxnzc8KEppqapG3b5vftzqVLpbffljo6pLo66Re/mF9d//APZn3kI6Yj1h/9kZSdPb89AQBJwuNhBCEAAAAmjY5KnZ3Tw1Xe464uu6uzzurV/l2sNm0y4auMDLurAwAAAACEiwAWECMHDhyYdr26utqvg9VsvMG0pqamsMcq1tXVqbm5WZIZx1hVVaWmpqawz4nEVlYmHT0q7d0rDQzM/flLl5rnf+xjZj3+uBlrWF8v/f3fz6+2Dz4wYxK/+lXpj/9Y+tKXpPXr57cnACDB9fWFbrlIBywAAICkMjEhdXf7wlVTQ1YdHdLYmN0VWmPlysDjAjds4ItpAAAAAJAsCGABMdDY2Ki2trbJ65WVlQHHEc6msrJS7e3tc+qY5XQ65XQ65XK5JEnNzc1qbW1VRUXFnM6NxLVzp/TOO1JV1dzGEW7ebDpolZX5bnM4pB07zHr/fenb35Zeesl8IzVSbrf0rW9Jf/VXJij27/6dVFHBeEIASEmhul9JdMACAABIQB6P9OGH/qMCvZd379pdoTVycgKPC9y4UbKw4T8AAAAAIE4RwELciaexgVZwuVyqra2dvF5RURFxF6q5jiv0nq+xsXHyel1dHQGsFFNWJp0+Lb3+unT4sBkpGMyOHaYz1RNPzN7mvqxM+u53pW98Q3r+eel//k/TuCRSExPSj35k1qZNpoYvfEFatizyPQEACSacABYdsAAAAOLWrVv+nay8l7du2V2dNTIyTNeqQEGre+7hC2UAAAAAkMoIYMF2ubm5luzjdrv9bsuLg6+XVVVVTdZWXl6ulpaWmJ5/9+7d0wJYra2tcrvdlv3ckRgyMqT9+806c0Y6dsx8zj0wIC1ZYj7P3rNH2rJlbvsWFkp/+ZdmlOD3vmc6WbW3z6/Wc+ekP/kT6T/9J+kP/9B0xZraiQsAkKSuXp39fodDKiiITS0AAAAI6M4d6cKFwCMDb9ywuzprpKVJ69f7jwvctEkqLpYWLLC7QgAAAABAPCKAleTa2tq0a9eugOGkWHE6nWppaYmoe1Oiq6qqmhw9WFFREfPwlRS4a9arr76q6urqmNeC+LBly9yDVqFkZ5ug1Be/KB09asYKvvPO/PYcGpIaGszavt3XmSsz05qaAQBxJlQHrPx8aSG/vgAAAETb6KjU2Rl4XOClS3ZXZ53Vq/27WG3aJJWU8N4DAAAAAGDu+AQjyfX29toavpLMCL7ZanA6nZMhJavZGfqqr69Xc3OzJKmysjLisYPzFajT1alTp2yoBKlgwQITknriCenkSemv/1p65RVpbGx++x4/btaqVdJTT0nV1VJpqTU1AwDiRKgOWIwfBAAAsMzEhNTd7d/F6vx5yeWSxsftrtAaK1YEHhe4YYOUk2N3dQAAAACAZEIAK8lVVFSor69PLpfLthqcTues4+5mjgmMNDDW29vrd5tdY/aam5tVW1srSaqurlZDQ4MtdQRj538PSB0PPSR9//tSfb30ne+Y9eGH89vzww/NfvX10u7dpuPW3r1Sero1NQMAbBSqAxYBLAAAgDnxeMxYwJkBq3PnzBjBu3ftrtAa2dn+ISvv9RlvOwIAAAAAEDUEsFJAbm6uysvL7S4jqNIZbWwCBanCESi4ZUcHrNbWVlVVVUmS6urqdOjQoXnt19bWpgMHDqitrU3l5eVqamqa0+uaGXCTIv8ZA5EoKpL+4i+kr35Vevll0xXr17+e/74tLWbdc4/0x38sHTggrVs3/30BADYJFcAqLIxNHQAAAAnG7Z4+JnDqZX+/3dVZIyPDdMIO1M2qsFByOOyuEAAAAACQ6ghgwXYzw2GRdsCa2dXJju5XLpdLu3fvliQ1NDSourp63nvu2rVr8mfS1tamrVu3qq+vL+znBwpbBQplAdG2aJH0hS9I/+bfmHGCf/3X0g9/aMYezMe1a9Jf/qX0jW+Yrlj/9t9Kjz9uzgcASCCMIAQAAAjq9m3TtSpQN6v5dpuOF2lp5otVU8NV3uO1a6UFC+yuEAAAAACA4AhgwXYPPvig321ut3vOAaqbN29Ou15RUTGvuubK7XZr69atkqSmpiZVVlaG9bzGxka1t7errq7O7z6Xy+UXSHO73XK5XGF3wQoUaLNrNCMgmW+l7thhVleX1NAgvfCCGYswHx6P9OMfm7V8ufT5z5sw1gMPWFM3ACCKPB46YAEAgJQ3Oip1dPgHrM6dk7q77a7OOkVF/l2sNm2SnE4pM9Pu6gAAAAAAiAwBLNguNzdXTqdzWgcrl8s157GJMztgPfTQQ5bUFw5v+Mrtds8pfCWZTlnBwlTBuoHNt4NVLH82wGyKi6Wvf136sz+TXntNev556d13579vX5/Z6/nnpfvvN0Gsz31OWrFi/nsDAKKgt1caGZn9MXTAAgAASWBiwnwZaWbA6vx5E74aH7e7Qmvk5U0PV029zMmxuzoAAAAAAKxHAAtxoaKiQo2NjZPXA43NC2VmWGkuIaj52rVrl1wu15zDV5IZK7h///6A9wUKZh06dGhOHaxmBtOk2P5sgHBkZEif/axZv/61dPiw9NJLZsTCfP3619LTT0vPPCN95jMmjFVRwegCAIgrocYPSgSwAABAwvB4pOvXA48LvHBBGh62u0JrZGcHD1nxBSgAAAAAQKohgIW4UFtbOy2A1dbWNucRgu+9997kcXl5edgj+uarqqpKbW1tEYevJAXt9uXtDpabm6uamho9+OCDc+4MdvLkyWnXnU5nzH42QCTuv19qbJTq66Xvfc+MKPzgg/nvOzIivfqqWWvWSF/4glmlpfPfGwAwT6HGD0qMIAQAAHGnr88XrJoZthoYsLs6a2RkmN+bpwasvMeFhZLDYXeFAAAAAADEBwJYiAtOp1MVFRVqbW2VJLW0tOjQoUNhP9/lck3rgFVTUxP2c2tra9Xa2iqn06m6uro5hZNqamrU3NyslpaWOQfGJOmVV16RFLjTlVdlZaXq6+u1b9++OXW+8mpubp52va6ubs57AHbIzZX+5E+kr3xFOn7cBLGam0NPqApHd7cZffj1r0u/+7vSU09Jv//75tu7AAAbhOqA5XBIBQWxqQUAAGCKoSHTtSpQN6ueHrurs0ZamrR+vX/AatMmae1aOkgDAAAAABAOh8fj8dhdBCBJra2t2r179+T1vr6+sANHtbW1qq+vl2TCTO3t7WE9b/fu3ZOhr7met76+XrW1tTp06FDQEYJTTR2r6Ha75XK59Nxzz8ntdmu2/xu63W4tX75c1dXVamhoCHmeqWb+TMvLy3Xq1Kk57WG3n//853r44Yen3fbuu+/qk5/8pE0VwU49Pb6uWBcuWLv3kiXSH/yB9Id/KG3bZt6ABgDEyHPPSV/9avD7Cwqka9diVw8AAEgpw8NSe7sJVs0MW12+bHd11ikq8g9YbdoklZRImZl2VwcAAACkLj4PBZIDASzElaqqqsmOTYcOHQqrW5Pb7VZJSclkB6xwu1G5XC6VBpg9VldXF7L7VnNzs6qqqkKeIxzhBMa8Ya+GhgZVV1eHvXdpaalcLpckM86wo6Mjoi5aduIfHAhkYkL66U9NEOuHP5RGR63dv7hY+uxnpc9/XrrvPmv3BgAE8OUvS88/H/z+Bx6Q/nl0MwAAQCRGRiSXyxewmrouXZKS5R3SFSsCjwvcsEHKybG7OgAAAACB8HkokBwYQYi48sILL6itrU0ul0v19fXav3+/ysvLZ33OgQMHJsNXhw4dimgU4FQ3b96c9f7W1lbLwleSQr4+ybyulpaWydGK4YSwdu/ePS189eabbyZc+AoIJi1N2rXLrJ4e6aWXpP/1v6T337dm/64uqb7erHvvNUGsz33OjF4AAERBqBGERUWxqQMAACS00VGps9M/YHX+vHTxovkyTzLIyQk8LnDjRikvz+7qAAAAAABITQSwEFdyc3N16tQp7dq1S21tbdq6dauamppUWVnp91i3260DBw7MuWOWl9PpVHl5udpmdFPwhpwCcbvdloavvHWEo6WlRbt371ZNTY0aGhr0wgsvBAxvtba2qqamZjJ85XQ61dLSEvZ5gESzcqX0la9ITz9tmqO8+KIJZN26Zc3+v/mN9OyzZm3fbsJYVVW8qQ0AlrpyZfb7CwtjUwcAAIh7Y2MmTBUoZNXZKY2P212hNTIyTNeqQN2s7rlHcjjsrhAAAAAAAExFAAtxxxvC8o7dq6qqUnl5uWpqauR0OuV2u3Xy5Ek1NjbK7XbL6XSqoaEhos5Xb775pqqqqtTa2jq5z2xBJZfLNdltyyoPPfRQ2I9taWmZ/Lls3bp1MkSWl5en3t7eye5hkvk5PvvssyHHKQLJwuGQtm4165vfNKMJX3xRevNN60ZJHD9u1pe/LP3e75muWHv3SllZ1uwPACmLDlgAAGCK8XEzFjBQyKqjw4SwkkFamlRSEribVXGxtGCB3RUCAAAAAIBwOTweqz6WBqzndrv16quvqqmpSS6XSy6XS7m5ucrLy1NFRYVqamrCGuGXbGb7uZSXl2v//v0Bu4YlImYeY746O6W//Vvpu98135K2Wk6O9OSTpjPWo49KC4k2A8DceDzSokXSyEjwx3znO9IsXUoBAEDimZgw499nBqwuXJBcrtn/aZBoVq8O3MnK6TSdrgAAAACkNj4PBZIDASwAcY1/cMAqExPSz35mumK99pp096715ygokPbvNyMKH37YfJsZABDCzZtmnuxsfvQj6bHHYlMPAACwzMSEdPmyf8Dq/HmpvV0aHra7QuusXDk9ZOW93LBBys62uzoAAAAA8YzPQ4HkQJ8OAEBKSEszHaoefVR6/nnp5ZdNGOvkSevOcf269N//u1mFhdLv/75UWSlt28boCAAIKtT4QYkRhAAAxDGPR7pyZXq4yrva26U7d+yu0DpLlvgHrLzHy5fbXR0AAAAAALATASwAQMrJzZW++EWz3n9f+v73pR/8QOrutu4cV6+aoNfzz0v5+WZMYVWVtGMHYwoBYJorV0I/prAw+nUAAICgPB7p2jX/gJU3dHX7tt0VWmfRIqm01D9gtWmT6XrscNhdIQAAAAAAiEd8BAwASGllZVJdnfTcc9Lx49JLL0lNTZLbbd05btyQvvMds1aulJ54wnT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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"helmholtz_volume.png\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Density of states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 1.55997070e-06, 2.49595390e-05, 7.64385915e-05,\n",
       "        1.55997128e-04, 2.63635149e-04, 3.99352655e-04, 7.29689360e-04,\n",
       "        1.19429119e-03, 1.54440394e-03, 1.93805976e-03, 2.40195090e-03,\n",
       "        3.07472737e-03, 3.70073302e-03, 4.34987128e-03, 4.99515119e-03,\n",
       "        5.65484469e-03, 6.37128858e-03, 7.29587302e-03, 8.35668687e-03,\n",
       "        9.29613678e-03, 1.03829867e-02, 1.15087211e-02, 1.26678989e-02,\n",
       "        1.38756496e-02, 1.51529836e-02, 1.65209545e-02, 1.78614549e-02,\n",
       "        1.93887225e-02, 2.11123556e-02, 2.29407136e-02, 2.47048673e-02,\n",
       "        2.63519431e-02, 2.83224667e-02, 3.02764831e-02, 3.23150126e-02,\n",
       "        3.45741100e-02, 3.70508322e-02, 3.94089045e-02, 4.18811547e-02,\n",
       "        4.46371517e-02, 4.73869699e-02, 5.01747787e-02, 5.31563335e-02,\n",
       "        5.62413129e-02, 5.95527931e-02, 6.30972160e-02, 6.68297098e-02,\n",
       "        7.06140716e-02, 7.43960691e-02, 7.85553956e-02, 8.28267773e-02,\n",
       "        8.72356496e-02, 9.21541835e-02, 9.72128345e-02, 1.02379127e-01,\n",
       "        1.07929623e-01, 1.13667849e-01, 1.19627212e-01, 1.26028927e-01,\n",
       "        1.32670915e-01, 1.39624618e-01, 1.47293697e-01, 1.55283949e-01,\n",
       "        1.63533630e-01, 1.72395710e-01, 1.81670126e-01, 1.91428460e-01,\n",
       "        2.02112086e-01, 2.13571838e-01, 2.25708138e-01, 2.38680538e-01,\n",
       "        2.52686579e-01, 2.67870233e-01, 2.84422946e-01, 3.02346174e-01,\n",
       "        3.22686165e-01, 3.45197546e-01, 3.71615301e-01, 4.02835584e-01,\n",
       "        4.42449106e-01, 5.11112155e-01, 5.53900357e-01, 5.60209161e-01,\n",
       "        5.69193454e-01, 5.75355216e-01, 5.83160278e-01, 5.89715546e-01,\n",
       "        5.97387259e-01, 6.05370050e-01, 6.12352028e-01, 6.20192431e-01,\n",
       "        6.28387855e-01, 6.35281282e-01, 6.43177585e-01, 6.50702853e-01,\n",
       "        6.58660125e-01, 6.66888279e-01, 6.74356694e-01, 6.82815235e-01,\n",
       "        6.90140891e-01, 6.98594660e-01, 7.06351576e-01, 7.14896103e-01,\n",
       "        7.23835197e-01, 7.31613273e-01, 7.40445285e-01, 7.49417604e-01,\n",
       "        7.57054774e-01, 7.65794099e-01, 7.74660780e-01, 7.55035225e-01,\n",
       "        6.86362095e-01, 6.53014760e-01, 6.27893329e-01, 6.07707821e-01,\n",
       "        5.90435473e-01, 5.72935577e-01, 5.56463426e-01, 5.40466589e-01,\n",
       "        5.10596572e-01, 5.10385602e-01, 5.08595784e-01, 5.04918910e-01,\n",
       "        5.01892862e-01, 4.98709642e-01, 4.93275109e-01, 4.88019722e-01,\n",
       "        4.83713315e-01, 4.76181511e-01, 4.69059356e-01, 4.62709115e-01,\n",
       "        4.53312769e-01, 4.43878685e-01, 4.34735956e-01, 4.21658960e-01,\n",
       "        4.10888791e-01, 3.96756837e-01, 3.80020990e-01, 3.64956570e-01,\n",
       "        3.45109714e-01, 3.10331872e-01, 3.00610474e-01, 3.46170030e-01,\n",
       "        4.15257287e-01, 5.13440920e-01, 5.72881903e-01, 6.27010738e-01,\n",
       "        6.77756223e-01, 7.27475982e-01, 7.71881416e-01, 8.19491391e-01,\n",
       "        8.62886272e-01, 9.07287907e-01, 9.50228111e-01, 9.92279455e-01,\n",
       "        7.68765254e-01, 6.54124079e-01, 5.74101622e-01, 5.09556625e-01,\n",
       "        4.53311886e-01, 4.01237668e-01, 3.51638278e-01, 3.03551996e-01,\n",
       "        2.53622708e-01, 1.99562116e-01, 1.30052745e-01, 3.28802469e-02,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "        0.00000000e+00]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_dict['density_of_states']['projected_dos']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dos = results_dict['density_of_states']\n",
    "\n",
    "fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "frequency = uc.get_in_units(dos['frequency'], 'THz')\n",
    "plt.plot(frequency, dos['total_dos'], '-', lw=3, label='total')\n",
    "for projected in dos['projected_dos']:\n",
    "    plt.plot(frequency, projected, 'r:', lw=3, label='projected')\n",
    "plt.xlabel('Frequency (THz)', size='xx-large')\n",
    "plt.ylabel('Density of states', size='xx-large')\n",
    "plt.legend(loc=2, fontsize='xx-large')\n",
    "plt.ylim(0.0, None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thermal properties - pull out temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_dict['thermal_properties'].keys()\n",
    "\n",
    "thermal = results_dict['thermal_properties']\n",
    "temperature = thermal['temperature']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Helmholtz and Gibbs free energies versus temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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diIga1tjqjD0AklT1dMuFZA32RFAwq65RrMg8iD9/sRv5JXUnX940sgfmXTsEPWPaWBQdEVnB5z0RAATAsyIyqjkfQkTWCg0RzBjbB1//4jI8fHkiIsJq/6//8ZYjuOIvX+NvabtR6rRPBxFRQxpLIqap6oMA4kTkiZYICABEJEVE0hxeJ4lItohkmo8FLq6Zal43y6HtVH3nE7VG7SPD8Iurh+DLxy/F9cO729vLq2rw/Jd7cOVfv8YnW46Ac6WIqCncmlhpLtvMVNWvfBeS/bPSVHWS+TxFVdPN50kAClU1x+HcFAAFqprl/Nx2XWM4nEGt0cbcAvzPJzuw40hxnfZx/WPxuxuH4vweHSyKjIh8rSWGM+pQ1T8DOCUiT5ilsFuEUyKQ4JhAmDIALDcTjARVzTLbY0QkoUWCJApA4/rH4uNHLsIztw5HXLsIe/vG3ALc8OIq/OrDbTh1psLCCInIn7ldXF9Vv1PVvwCYISK3+iCmeonILFVd4SKmQhiVNZfDKMFtEwugQEQW1/d+IpIhIhl5eXk+iZnI34WGCG4b1wdfPXEZ7ruoP8LMZZ81Cry9/gAu/+vXeHv9/jo1J4iIgGbWiRCR/gCmAFiuqvvduG6Wi+Ycxx4Hx+EMh7blqjrNxftNNa/PMuc/bHJMNly1OeNwBpFh74kS/M8nO7BqT36d9vO7d8DvbxmKMX1jLYqMiLzJG8MZDZatE5H5qvqUw+sOqN3FMwHGX/2JABaIyDyzh6JRqprqbqAiEtPA4QSHBGE+gOlmolJgtp909/OIWqsBXdrjzXvH4T87j+P3/9qJQ6dKAQA7jxZjyivrMCWpF568dgjioyMtjpSIrNZY7dtp5pyCJBhJA2As+wSMnTwzYGwDngYg11tBmT0LySIy1SE5iEXtzqG282y9Falm0pADI6FINZOOZHOiJRrqhSCiukQEVw/thksHxWPxNzl45Zu9KKusAQD8M+sQ/rPzGB6fNAg/uqAvtxwnasUaKzZVACAdxpdztvkzR1W9ljD4Cw5nENXvYMFZ/OHTnfhix/E67ed174A/cIiDKCD5fO8MEXlGVZ9szgcECiYRRI37ZncefvfxDuTmn6nTPj25F+ZdMwRx7TnEQRQouAGXFzGJIGqa8qpqvLoqFy9+tcc+xAEAHduEY941Q3Db2N7c2IsoALR4nQgiosiwUDx8+QCkPXYprjq/q729qLQST6/chimL1mKnU/EqIgpObiURInKliPzCudgUd/skan16x7ZF6o+T8fe7k9E7tnbzru8OFOLGl1bj9//aiZLyKgsjJCJfc7cnIkFV/2wu5bTXelDVV1u68BQR+YcrhnRF2mOX4idXDEB4qDGMUV2jeG11LlL++g0+336Ue3EQBSl3kwjHegtFTsc4CErUSkWFh+Lxqwbj859dggmJcfb2Y8VlmPN2Fu5/IwOHTp21MEIi8gV3k4hEEbncfO78pwX/1CBq5RLj2+Od+8fj/2aMQuf2tXtxfLnrBCY99y0Wf5ONyuqaBt6BiAKJJxtw/VlElgIYIyLRQJ1KlkTUyokIbhndE18+fhnuGN/H3l5aWY35/96FG19cjc0HCy2MkIi8xZMNuJIB7AMwA0ChiJyEUa2ySVtuE1Hr0LFtOP40eTj++eCFGNw12t6+69hpTF64Br/7eAcnXhIFuOZuwNURQGwwVLBknQgi36msrsFrq3Pxf+m769SW6NYhCv9781BcNbSbhdERtU4+rRPhuISzPqpa1FAC0ZT3IKLgFx4agjmXJiLtsUtxyaB4e/ux4jLMeisTc97KxPHiMgsjJCJPNDSckeUwidItItJBRL4AkOJZWEQUjHrHtsUb94zF87eNQly72omXn+84hpTnvsG7Gw6gpoZztIkCRUNJxFUAlojIJhGZ3JQ3E5FRIrIIxhyJ5ar6gTeCJKLgISK4eVRPfPnzSzE9uZe9/XRZFZ5euQ23LVmP7LwSCyMkoqZqdE6EiMyFUViqP8xdPGFsA27bljsWxsqMJPN1KoBnA22eBOdEEFljbXY+nv5gG/adrK0jEREWgp9eORCzLklAOLcaJ/KJFt2AS0QSAFwJIBFADIzEoRBGUnESQJaqftmcYKzEJILIOmWV1Xjhyz1Y/G0Oqh2GM87r3gHPThmB4b06WhgdUXDiLp5exCSCyHo7jxRj3j+3Ytvh2oK4oSGC+y/qj8cmDUJUeKiF0REFF+7iSURB5fweHbDyoQl4+rohiAwzfj1V1ygWf5uDa59fhY25BY28AxG1JCYRRORXwkJDMOuSRHzxs0twYULtPhy5+WcwffE6/PrD7SxSReQnmEQQkV/q17kd3n1gPObfOhzRkWH29rfW78fVf/sW3+7OszA6IgKYRBCRHxMR3D6uD/7z+CW4YkgXe/vhwlL8+O8bMXfFFhSVVloYIVHrxiSCiPxe945t8Npdyfi/GaPQqW24vX1ZxiFc/bdv8dWu4xZGR9R6MYkgooBg2x007fFLcf3w7vb2Y8VluPf1DDy+bDOKzrJXgqgluZVEiEiNiCxtagVLIiJv69w+Ei/PTMLCmUl1Smd/kHUYk/72Db78nr0SRC3F3Z6I6QAEwGsiUm0mFLf6IC4iogZdN7w70h6/FDeN7GFvO3G6HPe9wV4JopbiVhKhqitUdbqqxgK4GsApAM+aCcX77KEgopYU2y4CL9w+Gqk/GoPO7SPt7bZeCc6VIPItj+dEqGo6gGcALAbwJYxeij+bCcVCbgNORC3lqqHdkPbYJbh5VN1eiXtfz8Avlm9BcRl7JYh8we0kQkT6ich8EdkDIBvGdt/LVDVEVQcAGAigM4B0T4MSkRQRSXN4nSQi2SKSaT4WuLhmrnndXIe2qc5tRBScOrWLwPO3jcZip16J5ZmHWFeCyEfcnViZASNxmAZjt84Bqnq1qr5qO0dVcwA8CcDjetxmL4ejWFVNVNUxAB6A0fvhGNdcAIW268ykY6rDexWKSIqn8RBR4Lh6aDf857FLcMOI2hUcR4vK8OO/b8TTK7fhDKtdEnmNuz0RGQCSVXWAqv65ge2+T8JINLzCKalIMBMVR3Go3ZocMHpHxsLYYRTmzyQQUasQ2y4CL92RhJfvSKpTV+LdDQdwzfPfcg8OIi9xN4nor6rf1XdQRJ4Qkfnmef9sXmgu33+Wqq5wcWgxgLEiEgNjq3LA2K7cUZzTa4jILBHJEJGMvDx2dRIFm+tHdMd/HrsUVw/tam87WFCKGanr8MdPd6KsstrC6IgCn7tJRCIAiEgH54mTIrIUwNMAxgDIFJHL63sT88vb+dGU4YZJrhpVNUdV5wGIhTHckgOg0HxdL1VNVdVkVU2Oj49vwscTUaCJj47EojvH4G8zRiI6ytiDQxVYsioXN7y4GtsOFTXyDkRUn7DGT6kjXUROwvgrX0TENrGyEMbwRYqqfmXOR3gWxpDCOVQ11d1AzV6G+o4lwRhmSRWRsar6rIgAtb0RCQDS6rueiIKbiGDy6F64ICEOc1dsxao9+QCAvSdKMHnhGjx6xUA8dHkiwkNZxJfIHe7+PyYZwBIYf+HHms9XwPiSVlX9CsYTW5tHzCQk2TY50hSLuvMeYFvBoapZAArM8+c7xmDr4XAxWZOIWpnuHdvgzXvH4Q+3DEPbiFAAQFWN4m/puzH1lbXIziuxOEKiwCKq2vSTRWoAxKhqsVPbGAAZqhrq0F5gFqUKCMnJyZqRkWF1GETUQvafPIOfL9uCjP2n7G2RYSF48tohuOvCfggJEQujI/I9EclUVY9XUgLu90T8E8ASERkpIqPMeRBpAPqbAUWbP2+FsZKDiMgv9Y1rh6WzL8S8a4YgPNRIGMqravA/n+zEj/++EUeLSi2OkMj/uZtE3G9e8x2ATACdABTBmP/wJYB9IvIFgOUwqlkSEfmt0BDBg5cl4uNHLsKQbtH29tV783H1377FJ1uOWBgdkf9zazij0Tcz5zIAWNrQUlB/xOEMotatvKoaf0vbg8XfZsPx1+JNI3vg9zcPQ0eHehNEwcAbwxnuzokYpaqbm/OB/opJBBEBwMbcAjy2dDMOF9YOZ3TvGIW/Th+JCYmdLYyMyLusmBPxKnfqJKJgNq5/LD7/2cWYOqaXve1oURlmvroBf/x0J8qrWKCKyMbdJOIZGFt/Rzd6JhFRgIqOCsdfpo3Eojtry2bbClTd/NIa/HDstMUREvkHd4tN9QcgMCZQpqN2bwoAgKo+5a3AiIisds2w7kjq0wlPrNhq3wV017HTuPGl1XjymiG4ewKXglLr5u6ciGU4d08KG1XVq70SlQU4J4KI6qOqeHPdfvzps+9RXlVjb79kUDz+MnUEunSIsjA6Is+0+MTKYMYkgogas+f4afz0/c3YedRebw+x7SLwzK3DcdXQbhZGRuQ+KyZWQkT6ich8EXnfoe0JERnVnECIiPzdwK7RWPnwBMy6JAFijmIUnKnArLcy8fTKbSit4KRLal3cSiJE5AEYu2R2grHhlk0RgAVejIuIyC9FhoXi6evOwzv3jUc3h2GMdzccwA0vrsL2w9wVlFoPd3si5gKYpKpzYEywtFkGo8gUEVGrMGFAZ3z+s4tx3fDaYYzsvDOYvHANlnybg5oaDhVT8HM3iYiD0RMBAI7/D4lF3aSCiCjoxbSNwMt3JOHZKSPsu4JWViv++Nn3uOsfG3GiuMziCIl8y90kYjmAxSLSz9YgIh1g9EQs9l5YRESBQUQwfWxvfPqTizGiV0d7+6o9+bjm+VX4atdxC6Mj8i23kghVnQ0gFEZ9CBGRPQBOAchhjQgias36d26HFXMm4MHLEutMurz39Qz87uMdKKvkpEsKPh4t8RSRJABjzJfpqprr1agswCWeROQta/fm47Flm3G8uNzeNqRbNF68fTQGdmXBX/IPrBPhRUwiiMibCs5UYO6KrUj/vnY4Iyo8BL+5YShuH9cbIpxGRtZq8ToRInKFiOwRkWpXj+YEQkQUTGLbRWDJj8fgD7cMQ2SY8au2rLIGT6/choffzULR2UqLIyRqPnf3zkiFMR/iSQCF3g+HiCh4iAjuvKAvxvaLxaPvZWH38RIAwGfbjmHLwSI8f9soJPeLtThKIs+5u3dGAYAkVd3ns4gswuEMIvKlsspq/OHTnXh7/QF7W2iI4LGUgXjwsgEI5UZe1MKsKHu9DMDo5nwgEVFrFBUeij/cMhyL7hyDjm2M7cWraxR/+c9u/Oi1DTjOmhIUgNwdzigEsEJEsgCc82e7qj7olaiIiILUNcO6YUSvjvjp+99h075TAIC12Sdx7fOr8NdpI3H5kC4WR0jUdO72RCQA+BJGbYhEFw8iImpEj5g2eO+BC/CTKwfWqSlxz+ub8KfPvkeFw3bjRP6MSzxNnBNBRFZYm52Px5bWrSkxsncMXrp9NHrHtrUwMgp23AqciCjATUjsjH//9BJcPjje3rblYCGue2EV/r3tqIWRETWOW4ETEVkstl0EXrtrLH51/XkIM1dpnC6rwoPvZOFXH25jyWzyW365FbiIpIhImsPrJBHJFpFM83FOwiIic83r5jq0narvfCIifxISIrj/4gSseHACese2sbe/vf4Abl24Frn5ZyyMjsg1v9wKXFXTnZpiVTVRVccAeABOO4aaiUOh7Tpzbw8AmKaqY1R1nrdiIyLypVG9Y/CvRy/GdcO72dt2Hi3GDS+swkebD1sYGdG5AmIrcKekIkFVc5xOiQNQ4PA6xfwZIyIJ9b2viMwSkQwRycjLy/NStEREzdOxTTheviMJv795KCJCjV/TZyqq8dP3N+OpD7ZyeIP8RkBtBS4is1R1hYtDiwGMFZEY1F1qGgugQERcJjiqmqqqyaqaHB8f7+oUIiJLiAh+dGE/fPDQBPSLq12l8d7Gg7jl5TXIziuxMDoigyVbgYvILBfNOY49DiKSpqqTnK5brqrTzr3UfjwBwFTzvVY4tC8AsKmeBAQAl3gSkf86XVaJp1duxydbjtjb2kaEYv6tw3HzqJ4WRkaBzBtLPN2tWAkAUNUsAFmefqiqprp7jdnLUN+xJADJqpoqImNV9VkzUSkwE4eTnsZKRGS16KhwvHDbKFyYEIfffbIDFVU1OGsOb6zPOYnf3jgUUeGhVodJrZDbdSJagpUe6HYAAByRSURBVIhMBZBs/rSJRd15D7Ct4DCTmgLz/Pnm4WUACkUkxTyn3l4IIiJ/JyK4Y3wffPjQRPTv3M7e/t7Gg5i8cC1yOLxBFmDFShOHM4goUJSUV+GpD7bVGd5oHxmGZ6YMxw0jelgYGQUSSypWEhGRtdpHhuGF20bhj5OHISLM+DVeUl6FR979Dr/9aDvKq7h6g1oGkwgiogAkIpg5vi8+eHAC+jqs3nhj3X5MW7QOBwvOWhgdtRbcO4OIKIAN69kRnzx6Ea4ZWlucauuhIlz/wiqk7zxuYWTUGnDvDCKiANchKhyv3JmE39xwvn3vjeKyKtz/Zgae+fcuVFVza3HyDb/cO4OIiNwjIrj3ov5YNudC9OgYZW9f9E027nh1A04Ul1kYHQUrv9w7g4iIPJPUpxP+9ZOLcemg2iq8G3MLcN0Lq7EumyVzyLsCYu8MIiJquth2EfjH3WPxxFWDYI5uIL+kHDNfXY+FX+9FTQ2X9pN3eGvvjNyW2DuDiIiaJiRE8MgVA/HWfeMR1y4CAFCjwLOf/4BZb2Wg6GylxRFSMHB7dYa5n8UYALMBPAtggKpO93ZgRETUfBMHdManP7kYyX072dvSvz+BG15ahe2HiyyMjIKBR0s8AUwHkKKqS1Q1l0s8iYj8V7eOUXhv1gW4/6L+9raDBaW49ZW1WLbpoIWRUaBrzhJPx30tuMSTiMiPhYeG4Fc3nI9FdyahfaSx92JFVQ3m/nMr5q3YirJKVrkk93GJJxFRK3LNsO74+JGJGNw12t62NOMgpryyFgdOssoluYdLPImIWpmE+PZY+fAETB7d096240gxbnhxFf6764SFkVGg4RJPIqJWqG1EGJ6bPhK/v2UYwkNrq1ze8/omPJe2G9VcBkpN4K0lnjlc4klEFFhEBD+6oC+Wzb4Q3R2qXL7w5R7c8/omnDpTYWF0FAg8XeKZjLpLPGd4OzAiImoZo/t0wr8evQgTB8TZ277dnYcbXlzNZaDUIHdXZ4wCAFXNMpd3LlHVXN+ERkRELSWufSTevHc8Hros0d52uNBcBprBZaDkmrs9Ea+KyGSfREJERJYKDRHMvWYIUn80BtGOy0BXbMUvV25DeRWXgVJd7iYRzwB4VkSiGz2TiIgC0lVDu+GjRyZiUNf29rZ3NhzAjMXrcbSo1MLIyN+4m0T0h7GUc5+ILBWR+Y4PH8RHREQWSIhvj5UPTcQNI7rb2zYfLMSNL67G+hzuBkoGd5OIsTBWZmTCqFo5xuGR5N3QiIjISu0iw/Di7aPxq+vPQ6i5HWh+SQVmvroBr63OhSqXgbZ20tA/ArN3Yb6qFrdcSNZITk7WjIwMq8MgIvJL63NO4pF3s5BfUrvs86aRPfDMlOFoGxFmYWTkKRHJVNVmVZturCdirtMHvtKcDyMiosB0QUIcPnn0IozqHWNv+3jLEdy6cC32nzxjYWRkpcaSiFwYQxU2s3wYCxER+bHuHdtg6ewLcMf4Pva2XcdO48YXV+PrH1guuzVqLImYA+BLEdljVqeE7bmrh+/DJSIiK0WGheJPk4djwZThiAg1vkJs5bJf/u9ezpNoZRocyFLVdBHpBCAFxuZbi2BUqSQiolZsxtg+GNytA+a8lYljxWVQBf78xQ/YdqgIf5k+0r7dOAW3BidWnnOyyCJzG3CfEpEUAPPMEtu2tqkACgEkqGqqi2tsx5NU9dn62urDiZVERO7LO12Oh9/NwsbcAnvbwC7tkfrjZPTv3M7CyKgxLTGxso6WSCDMz0l3fG0mFTlme46IJDkdn+pwXaGIpLhqa4nYiYhak/joSLxz/3jcM7GfvW3PiRLc9NJqbiveCri9AZdFMgAsN5OHBFXNcjpuq18B82dSPW11iMgsEckQkYy8vDzfRE5EFOTCQ0Pw2xuH4rnpIxEZZnytnC6rwr1vcJ5EsAuIJEJVCwEsBrAcQKKLU2KcXsfV0+b8vqmqmqyqyfHx8V6JlYiotbo1qRdWzJmAHua24rZ5Eg+9k4Uz5VUWR0e+YEkSYfYAOD/qHW4whybSVTXR4bWjQgCxTWgjIiIfGt6rIz559CJckFD76/ff24+xnkSQsiSJMHsAnB/pDVziOIQxH+cmB5tQ2/OQACCtnjYiIvKxuPaReOu+uvMkfjh+Gje9tAbf7ubQcTDxy+EMs6ch2aHHIdWht2K6bXWGiKQBgKquAJBg681Q1XRXbS3+H0JE1ErZ5kn8ZdpIRJjzJIpKK3H3PzYi9dtszpMIEu4u8bwCQIGqbjZf3w9gGoyJi/MCeY8NLvEkIvKNLQcLMdusJ2Fz86geWDBlBKLCQy2MrHVr8SWeABbAGBqAiEyBMdnxOxiTHZc1JxAiIgpOI3vH4ONHJyK5byd720ebj2DqorU4XFhqYWTUXO4mEUkAbMMCs2FMdnwSRnnsSfVeRURErVqX6Ci8+0DdfTe2Hy7GzS+trlOoigKLu0lEEQBbKpkCY8klACiM1RBEREQuRYSF4E+Th+MPtwxDWIgAAPJLKnDHkvV4e/1+i6MjT7ibRCwBkGVutlWoqq+a7VMBZHo1MiIiCkp3XtAX7z5wAeLaRQAAqmoUv/pwO365chsqqmosjo7c4W7Z63kAZsDYhKufw6EcAPO8FxYREQWzcf1j8fGjF2Fojw72tnc2HMCdr23AyZJyCyMjd3iyxHMvjMmVS0RkqYj8HECaqn7n3dCIiCiY9YxpgxVzJuCGEd3tbRtzC3DTS2uw40iRhZFRU7mVRJgrMrJhLOsU8/FLAKdEZKT3wyMiomDWJiIUL94+Gr+4ejDEmCaBw4WlmPrKOny27ai1wVGjPJkTsURVB6jqdPMRC+AD8xgREZFbRAQPXz4Ar/44Ge0jwwAApZXVeOidLDyXths1NSxM5a/cTSIKADzjon0egGYVrCAiotbtyvO64sOHJ6BfXFt72wtf7uEGXn7M3SQiHUB/F+39AKxodjRERNSqDegSjY8evggXD+xsb/t8xzFMeWUtDhactTAycqXBstciMt+pKRHAlTi3OuV0AMtU9UHvhtdyWPaaiMh/VFXX4E+f7cLf1+Ta22LbReCVmUkYnxBnYWTBoyXKXo9xesTAqAeR6PTIBLfdJiIiLwkLDcFvbjwfz04ZgfBQY8ZlwZkK3PnaBry/8YDF0ZFNWEMHVfWqlgqEiIjI2fSxvZEQ3w5z3s5EfkkFKqsVT36wDT8cP41fXncewkL9cjPqVsPtuy8i/URkvlkjYqmI/FxEon0RHBERUXK/WHz0yEU4r3ttYap/rNmHe17fhKKzlRZGRt6qE1HIOhFEROQrPWPa4J8PXohrh3Wzt63ak4/JC9cgJ6/EwshaN0/qRKSyTgQREbW0thFhePmOJPz0yoH2tpz8M7jl5TVYvSffwshaL0/qRCxw0c46EURE5HMhIYLHJg3Cy3ckISrc+AorLqvCXf/YiDfX7UNDKw7J+1gngoiIAs71I7pj+ewJ6NohEgBQXaP4zUc78KsPt6OymjuBtpQGV2e4qBMRC2CFiLisE+HNwIiIiBoyvFdHfPzIRZj1Zga2HDI27HpnwwHk5p/BwplJiGkbYXGEwY91IoiIKGB17RCFpbMvxE0je9jb1mafxOSFa5HNCZc+12DFytaEFSuJiAKXquKlr/bir2m77W0dosLw8swkXDww3sLI/FdLVKwkIiLyeyKCR68ciIUz6064vPsfm/DWun2WxhbMGpsT8QqA5ar6lfnaeY5EHar6lBdjIyIicst1w7ujd6e2eODNDBwrLkN1jeLXH+3A3hMl+PUN57PCpZc1djcnAUhweO08R8LxkeSLAImIiNwxvFdHfPTIRIzo1dHe9sa6/bj3jQwUl7HCpTdxToSJcyKIiIJLaUU1nli+BZ9uO2pvG9ClPV67Kxl949pZGJl/CNo5ESKSIiJpTm1TzfZZ9VxjOz7Xoe2UiGSKiKsCWUREFMTaRITixdtH4ycOFS73nijBLS+vwcbcAgsjCx4NJhEi0l9E7q/n2FKnxyhvBaWq6U6flQIgx2zPEZEkp+NTHa4rNM8HgGmqOkZV53krNiIiChwhIYLHJw3C87eNQkSY8ZV36mwlZr66Hv/MPGRxdIGvsZ6IeTA223JlGoBT5iMRwGwvxuUsA8ByM3lIUNUsp+NjAeSYz3NQOz8jRkQSQERErdrNo3ri/VkXoHN7owBVZbXi58u34M9f7EJNDYf1PdVYEpECYHF9B1V1jqrOAfCkea5PqGqhGcdyGAmLsxin13Hmz1gABSLi8r9BRGaJSIaIZOTl5XktXiIi8j9JfTrhw4cnYnDXaHvby//NxsPvZqG0otrCyAJXY0lEAgDnv/ptHIccslF3FUeDzC9v50e9SYg5XJGuqokOrx0VwkXFTFVNNROQQhfX2I4nq2pyfDyLkRARBbtendpixYMX4vLBtb/z/739GGakrsOJ4jILIwtMjSURhQBGuzqgqlc5vEwyz20S88vb+ZHewCWOQxjzcW7CsAm1vREJANLMxMSWOJxsamxERBTcoqPC8epdY3HPxH72tq2HinDLy2uw80ixdYEFoMaSiOUAnm7C+8yGFzfgMr/8kx2SgFSH3orpqppqnpcGAKq6AkCCrTfDTEiWwWGSpXkOERERQkMEv71xKH5/yzCEhggA4EhRGaYtWouvdh23OLrA0WCdCBHpCGNzrb0AZqvqfqfjHWBsAT4GQH9VDdgUjnUiiIhap2925+GRd7JwurwKABAiwK+uPx/3TOwHEbE4Ot/xeZ0IVS0CcBWAgTCWVn4hIq+Yjy9grMxIAJAcyAkEERG1XpcOisc/H5qAXp3aAABqFPjff+3Ebz/egarqGouj82+NFptS1RxzQuODAIpglMKeBEAAzFHVAaqa69swiYiIfGdQ12h8+PBEjO5Tu9jvzXX7cf+bGTjNUtn1YtlrE4cziIiorNIolf2vrbWlsod0i8Zrd49Fz5g2FkbmfUFb9pqIiMgKUeGheOG20Xj0igH2tl3HTuOWl9dg66EmL0JsNZhEEBEROQgJEfz8qsH4y7SRCA81JlbmnS7H9MXr8MWOYxZH51+YRBAREbkwdUwvvHXfeHRsEw4AKKuswZy3M7Hk2xxwKoCBSQQREVE9LkiIwwcPTUDfuLYAAFXgj599j19+uJ0rN8AkgoiIqEGJ8e2x8qGJSO7byd727oYDuPcNrtxgEkFERNSI2HYRePv+8bhpZA9727e78zBt0TocKSy1MDJrMYkgIiJqgqjwUDx/26hzVm5MXrgG2w8XWRiZdZhEEBERNZGIsXLj2akjEGbuuXG82Fi50Rr33GASQURE5Kbpyb3x5r3jEB0VBgA4W1GN+9/IwFvr9lkaV0tjEkFEROSBCQM644MH6+658euPduCPn+5ETU3rWALKJIKIiMhDA7tGY+VDEzGyd+2eG0tW5eKhd7JQWlFtYWQtg0kEERFRM8RHR+L9By7AVed3tbd9vuMYbl+yHvkl5RZG5ntMIoiIiJqpTUQoXrlzDO6d2N/etvlgIW5duBbZeSUWRuZbTCKIiIi8IDRE8Jsbz8fvbjwf5sINHCg4iymvrMWmfQXWBucjTCKIiIi86O6J/bH4R8mICje+YgvPVmLmqxvwyZYjFkfmfUwiiIiIvGzS+V2xdNaF6Nw+AgBQUVWDR9/7Dou+yQ6qzbuYRBAREfnAyN4xWPnQRCTEt7O3PfPvXfj1R8GzeReTCCIiIh/pHdsWHzw4AeP6x9rb3l5/ALPfysTZiioLI/MOJhFEREQ+FNM2Am/dNw43Omze9eWuE5ixeD1OnC6zMLLmYxJBRETkY5FhoXh+xig8eFmivW3b4SLcunAt9p4I3CWgTCKIiIhaQEiIYN41Q/DHycPsS0APnSrFlFfWYmNuYC4BZRJBRETUgmaO74tX70pGm/BQAEBRaSXufG0DPt161OLI3MckgoiIqIVdMaQrls6+oM4S0IffzcKrq3ICagmoXyYRIpIiImlObVPN9lkeXDPXl/ESERG5a0Svc5eA/uHT7/E/n+xEdYDsAuqXSYSqpju+FpEUADlme46IJDXhmqkO7YXmexAREfkN2xLQsf062dteX7sPD7+ThbJK/98F1C+TCBcyACw3k4cEVc1qwjVjAeSYz3MAnJN4EBERWc1YAjoe1w/vbm/7fMcxzHx1A06dqbAwssYFRBKhqoUAFgNYDiCxkdNtYpxexzmfICKzRCRDRDLy8vKaGSUREZFnosJD8eLto3H/RbW7gGbuP4Upr6zFwYKzFkbWMEuSCPPL2/lR73CDOTSRrqqJDq8bUwggtqETVDVVVZNVNTk+Pt6t/wYiIiJvCgkR/OqG8/HrG86HmEtAc/LPYPLCNdh2qMja4OoRZsWHqmqqm5ckqOoK8/l8ANObcM0m1PZGJABIa+BcIiIiv3DfRf3RvWMUfrZ0MyqqapBfUoEZqeuwcGYSLhvcxerw6vDL4QyzpyHZocch1aG3YrotCXFcjeF8jZl0JNh6OJwnXhIREfmr64Z3x9v3jUfHNuEAgLMV1bjvjQwszzhocWR1SSCtR/Wl5ORkzcjIsDoMIiIiu70nTuOuv2/C4cJSe9vPJw3CI1cMgNjGPDwkIpmqmtyc9/DLnggiIiICBnSJxgcPTcB53TvY2/6athtPr/SP7cSZRBAREfmxrh2isGz2BZg4oHaR4XsbD2DO25korbC2lgSTCCIiIj8XHRWOf9w9DpNH97S3pX9/Ane8uh4FFtaSYBJBREQUACLCQvDXaSMx59LacknfHSjEVAtrSTCJICIiChAhIYInrx2C393oXEtiLbYfbvlaEkwiiIiIAszdE/vj5TuSEBFmfI3nl5TjttT1WL0nv0XjYBJBREQUgK4b3h1v3TsOHaKMupEl5VW45/WN+Gjz4RaLgUkEERFRgBqfEIflcyagW4coAEBlteKn72/Gkm9zGrnSO5hEEBERBbDB3YxaEgO7tLe3/fGz7/H7f+1ETY1vC0oyiSAiIgpwPWLaYMWcCRjbr5O97bXVufb9N3yFSQQREVEQ6Ng2HG/dNx5XD+1qb/t4yxHc+/omlJRX+eQzmUQQEREFiajwUCycOQYzx/ext63em4/bUtch73S51z+PSQQREVEQCQ0R/OGWYfj5pEH2tu2HizHllbXYl3/Gq5/FJIKIiCjIiAgevXIgnrl1OELMolQHCs5i4dd7vfo5TCKIiIiC1G3j+mDxj5IRGRaCsf064X9vHubV9w/z6rsRERGRX5l0flcsnX0h+se1Q1R4qFffm0kEERFRkBvVO8Yn78vhDCIiIvIIkwgiIiLyCJMIIiIi8giTCCIiIvIIkwgiIiLyCJMIIiIi8giTCCIiIvIIkwgiIiLyCJMIIiIi8oioqtUx+AUROQ3gB6vjCHKdAeRbHUSQ4z1uGbzPvsd77HuDVTW6OW/Aste1flDVZKuDCGYiksF77Fu8xy2D99n3eI99T0QymvseHM4gIiIijzCJICIiIo8wiaiVanUArQDvse/xHrcM3mff4z32vWbfY06sJCIiIo+wJ4KIiIg80uqTCBGZKiIpIjLX6liCgYjEmPd0qogscGg/5z7z3jcf77HviEiS7d+yQxvvsRc53LtZLtp4j5vBvF9pTm1Nurfu3O9WnUTYfjmoajqAQhFJsTikYDAdQKyqrgAAEZnl6j7z3jefec8SzOe8x973lPnvOEFEEniPvcu8VznmvcuxJW0A77E3mPfLrqn31t373aqTCABjAeSYz3MAJFkYS1BQ1VRVtU3WSQCQDtf3mfe+GUQkAbX3D+A99irzL+M0EUlQ1WdVNQe8x96WAWC5iCQBSFDVLPAe+1JT761b97u1JxExTq/jLIkiCJlfcgXmL19X95n3vnkSzHtrw3vsXYnmo0BEFotIDHiPvUpVCwEsBrAcxr0GeI99qan31q373dqTiEIAsVYHEaSmqups87mr+8x77yERSXHuqgTvsS9km190mQBmgffYq8xu83RVTXR4zXvsO029t27d79Ze9noTarOuBABpDZxLTSQiU1X1WfN5Clzf5xgXbdQ0BeZ9jYExXp8E3mNv24TaX6QxMH6xOvaq8R43X4Jt7hSA+TDmU/Hfse809d66db9bdU+Ew6SpFPO181935CbzXi4QkUwRyQRc32fee8+papZ5v2Jh/p+d99i7zHsX43DvUnmPvS7VnHidAmA677F3mT07yQ4TJZt0b9293yw2RURERB5p1T0RRERE5DkmEUREROQRJhFERETkESYRRERE5BEmEUREMAqkiUi2WVjKG++X5rjvBlEwYhJB5GfMZW+nmvCY1fi7kRvSAMw2C0zZmcnFAhFRc+nyAhfHT5kJiOOGRdMALDGrtxIFJS7xJPIz5l/CjhXjkmCUBp4GIMuhvcD5C488Y375z1DVMfUcjwFwCsAYc48Hx2NJAFJsBdacji0AkKSqk3wQNpHlmEQQ+TnzSyoTLr7AgoHZ5b/AVv7YohiyAcxzqKDofHwqgOWqKi7ac+r738Uh+ejEhI+CEYcziKhVM4cbEupLIEyTYOxI63jdLBh7P9Sb2JmJQxaMks5EQYdJBFGAM3eZtI3Jz3JoX26O5TseTzEf2eYY/3IX72W7JtvV3ItGPm+uiEw15w4kme2212peM9XhmjQYQzUJ5nG1TWw0JyYudjg3RUS0sc9rKMZ6pKDutur1nZNmvneMiMw1yzQ3pXchA0YSQhR0mEQQBTDzSzgBwBgAswEsdpjIFwNgLowvvzEwviiXA5gH40ttGoCpTisIEmDsWJmG2r++7e/ZhM+bDWABgPkOf6HHAngAQCfz2HLbNeZcgdkwhgTEfDS129/l5zUSoyuJaCCJMJOaBADpZqLyJYAZTYwRALLN64mCDpMIogBlm9AHY0VBjrlRTiqML06bLFVdoao5ABbD+OJdYJ6/AsaXp/MX3DLbNao6DcYOlrOb+HmxMOZu2IcGzL/Ys1S1UFVTzfdL8dJtqPN5TYzRmW2XzvrYYrXdp3kAktxYdVEIJhEUpFr7VuBEgSzZ/JktUme+n+PYfobD88J62uIa+Zx0GF+CTfm8dFc9CeaQwiTzfRy3Gm4u589rSozOEtDwcMZY87j9s0QkB0Yy0VByYlMA7/33EvkVJhFEgS3H3VUNzVwl0NjnnfNlLMaW8AUwhh0yYKw08RZXX/7u3pPG7kcKgBVO920BjJ6dpiQRTfkMooDE4QyiwJUOY0Kir//KTQGwyZPPM4cXkgBMU1WXvRSm2HraHTXlcz25JzmNfH4SzEmVDpYB9h6WxsTCSKKIgg6TCKIAZc5zWAHgS7NqYoxZ7XJuY9c2Yrq5EiLBnKQYAyDVw8+z9RTMsp2Pc+cH5ACIEZEkc6WFLQEoBJBsXpcA4KnGAvcwxpMuYgJgrAgx37fO8k4zGUqFMaTRmAYnbhIFMiYRRAHMnPiYDmOIIBfGiov0Bi9qXDqMbvpM1E5cLPTk88zrnoXR/Z8L4ws1Cw7d++YXdA6MVQ+zUdsrsBjGl3suaocPGv0y9uCeZMHobajDrDa5wPbcsXfDTC5SYPR6LG+k5yMJdSuNEgUNVqwkIjuz5yFHVZs61h8UzPoTPqkIKiKnAFwZjNVGidgTQUTU+DJQj9hqcDCBoGDFJIKIyBi2mO6DSapPwSi0RRSUmEQQUatnTsicB6Oip1eYkzltRb2IghLnRBARmczhh4aWorr1XkwgKNgxiSAiIiKPcDiDiIiIPMIkgoiIiDzCJIKIiIg8wiSCiIiIPMIkgoiIiDzCJIKIiIg88v+ZTVlNNouDjAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "energy_unit = 'eV'\n",
    "#energy_unit = 'kJ/mol'\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "helmholtz = uc.get_in_units(thermal['Helmholtz'], energy_unit)\n",
    "plt.plot(temperature, helmholtz, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Helmholtz free energy (${energy_unit}$)', size='xx-large')\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "gibbs = uc.get_in_units(thermal['Gibbs'], energy_unit)\n",
    "plt.plot(temperature, gibbs, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Gibbs free energy (${energy_unit}$)', size='xx-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Entropy and heat capacity versus temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CF6YP1Wx7ERf4OsJfZ619xbvBGJMKPG2M2WOt3eu3ykQkJJRVVrNi/UGe/WgPewrPNHn+kjFJ3HdJKpeOSdJsexEX+Rr4/Rs3WGvzgauNMd8HfuWXqkQk6J04U8Gy1ftYtnpvk01soiMNN00byn2XpDB+UJw7BYpIAz4Hfivr4/t8Hd8Ys9hau8j5vXZeQLq19jFfjyUiXeNQyTn+8GE+f117gHOVDSfixfWM4u4LRnLPRaO0U51IkPEp8K21jxtj3jbG3AY8XXvd3hgTB6T4cizn1r5U5/e5zvGzjDGpxphM504AEQkSu46d4un38/j7xsNUNZqJNzS+F/fOTuG2mcPpG6MVu0WCkc//Z1prrzbGPAi8Y4yxeEblAFe19xjOdf98r6aZwEvO7/lAOl63/YmIezbsP8FT7+WxctuxJs+NHxTLA5elcf2UwURrExuRoNbR+/Afo37RHay1G3w8RKozmq993Pgm3MTGbzDGLAAWAIwYMcLHjxMRX1hr+Ti3iKfey+WTvKImz89KSeCBy9O4fGyyJuKJhIhOnXvrQNDTwun6EiChjc9aCiwFyMjIsK29VkQ6xlrLO9uP8+S7uWw80PTWujkTB/K1y9NIH9Fk/q6IBLlOX2xzRvlXAUvbuatesXP9Ph5INcakA+uoH+WnAis7W5eItF9NjeVfW47y5Lu5bD/S8H/jyAjDTVOH8MDlaYwdGOtShSLSWb4uvHMrsBg4QdPNc+4D/tDWMay1Oc6xFuCEvLV2hTHmQeeLAJqwJ9I1qmssb3x2mCdW5ZJ7/HSD53pERjAvYxgPXJbG8ITeLlUoIv7i6wh/jvOT6vy51BjTH0/4F9OOwK/lfYreeaxb8US6SFV1DX/fdJgnV+WS32ixnF7Rkdw1awT3X5qqpW9FuhFfA3+ls27+HuAd4IfOjPvpaFa9SNCrqq7h9Y2HeWLVbvYWnW3wXN+YKL504Ui+OjuFxL4xLlUoIoHSkc1z4ryv1Tsr7eW38hYRcVntiP6JVblNlr+N7RnFVy5O4d6LRxHfu4dLFYpIoPm68M4rxpjvG2PWa7MckeBXe43+t1m7m5y6j+sZxX2XpPLli0bRr1e0SxWKSFfxddLe00AmkGCM6YczcQ/IstZuDEB9ItIBNTWWt7Ye5f9l7WLXsYaT8WqD/p6LRxHXU0EvEi58PaW/3lr7AIAT+Jl4Ju89YIyx1tox/i5QRNrPWsuqHcf5zcpdbD3c8Pa62J5RfHV2Cl+5OEUjepEw5GvgF9f+Yq0tBV5xfkTEZavzinj8rR1N9qLv0yOSe2encN/sVPr1VtCLhCtfA7/EGDNNp+9FgsdnB0t4/K2dfLi7sEF7z+gIvnzRKBZemkZCH03GEwl3HVlpb4UxZiXwMpDdztX1RMTP8gpO86u3dvKvLUcbtPeIjODOWSP4+hVpDIjVffQi4tGRhXcWA2nAY0C6MSYPz+S9l51V90QkgI6WlvHbd3axPPsg1V7b1EYYmDtjGN++agzD+mtlPBFpyNfAzwPWWWufqW0wxlyFZzvbeYACXyRASs9V8vT7eTz30R7Kq2oaPHfd5EF8d844Rg/o61J1IhLsfL0P/xljTIox5sra0by19h08q+6JSACUV1Xz/Kf7eWLVbkrOVjZ47uLRiSy6djxThjXeYVpEpKEWA9871L15La0rIgFUU2N5Y/MRHn9rBweKzzV4bvLQfiy6djyzxyS5VJ2IhJrWRvjGWWinP/CStfbVLqpJJOyt21vMz9/YxqaDpQ3ahyf04gfXjOfzkwcTEWFcqk5EQlGLge99qt4Yc6sxZjlQhCbniQTM3sIzPPqvHfx7a8OZ9/G9o/n2lWO464IRxERFulSdiISydl3Dt9a+ArzirK433xjzAJ4JfC/pnnyRzis9V8n/vLObZav3UlldP/O+R1QE916cwtcuT9PqeCLSKb5O2isFngGeccJ/gTHmYTzhv8Rau9f/JYp0X1XVNfxl3QF+8/ZOTjSakHfj1CH84JpxDE/QLXYi0nkdWXgHqAv/xwGMMSnAPGNMBrAOWKoFeURa9+HuAn72xrYmm9tkjOzPI9dPYPqI/i5VJiLdUYcD35szc782/KcDDztfAhZp1C/S0P6is/zszW2s3HasQfvQ+F48fN0Erps8CGM0IU9E/Msvge/NWrsB2ODv44qEujPlVTz1Xi7PfLiHCq+Fc3r3iOQbV4zmq7NT6BmtCXkiEhitBr4x5vvW2l91VTEi3ZG1ln98doRfvLmdoyfLGjw3d8YwHrxmHAPitOa9iARWWyP8hYACX6SDdh49xY//voVP84sbtE8dHs9Pbpio6/Qi0mXaCvzE9o7yjTFxmqgn4nGqrJL/ztrNHz/Z22CDm6S+MSy6dhy3pg/Twjki0qXaCvwZQLwxZlo77rd/BrjNP2WJhCZrLX/fdJifv7mdglPlde2REYZ7LhrFf2SOIban7qcXka7XauA7s+9rV9rLb24Eb4y5D/ghkBKYEkVCQ17BaX70+hY+zi1q0D4rJYGf3jSJcYNiXapMRMSHlfaMMffjGcVjjBkFLAIWOC95BsgMQH0iQa+ssprfvZvLkvfzqaiun30/IDaG//z8RG6YMli32YmI69p9W56zNe4PgPlAOp4d8x4AlltrS40xVwWoRpGg9eHuAh752xb2F5+ta4swcM9FKXxnjk7fi0jwaOu2vF9aax/yaqq9Tn+1s7lOncaPRbqzwtPl/PyNbby28XCD9ukj4vn5zZM4b0g/lyoTEWleWyP8TGPMX621mwCstSXOqX3bxvtEuiVrLcuzD/CLf+6g9Fz92vdxPaNY9Lnx3DFzhGbfi0hQas8s/Rzn+mMWsNL5M7XxJD7dlifd3d7CMzz06mZW5zeclHfj1CH8389PJDk2xqXKRETa1lbgPwb8EpiDZ1LeA06bBfKNMSuAt6217wIPOT8i3UpVdQ1/+GgP/2/lLsq9lsQdntCLn900icvHDXCxOhGR9mkr8Jc4u+KtcH5wtsXNBGbi+SKwyBhTe4pfgS/dytbDpSx65TO2HKo/eRUZYbhvdgr/kTmWXj209r2IhIZ23YffqK0UeMX5AcAYkwk86vfqRFxSXlXNk6ty+f17eVR5rZQ3cXAcj82dwqShmpQnIqHFX9vjZhljsvxxLBG3bTpQwg9WbGqwT31MVAT/kTmW+y5JIToywsXqREQ6xm/b41prf+ivY4m4oayymv/O2s3SD/LwGtQzc1R/Ft86hdTkvu4VJyLSSS0GvjHmSmvtqq4sRsQtmw+W8t3lG9l9vH5U3ys6kkXXjuNLF47SrXYiEvJaG+EbY8zTQH/gJWvtq/76UOeaP8Aca+0ip20uUAKkW2sf89dnibSmoqqGJ9/N5Xfv5jbY1e7C1EQW3zqFEYm9XaxORMR/Wgx8Z+W8d6Bu85zlQBHwcmdG/saYdJygN8YsMsak4lmqt3YuQKoxJtNaqzkBElA7j57iOy9tZNuR+hn4vaIjeei68dw9a6RG9SLSrbR78xzgFeeWvPnGmAeAPDwj/7a2zW18rBw8i/nEA/nW2nxjzELgJecl+Xi+ACjwJSBqaizPfrSHx9/a2WCzm5mj+vP43KmMSurjYnUiIoHh06Q955a8Z4BnnPBfYIx5GE/4L7HW7vXhcBl4TuEDxDd6LrHxi40xC3B25xsxYoQvZYvUOXjiLN9/eROf5hfXtfWIiuDBa8bxlYtTiNSoXkS6qQ7P0nfC/3EAY0wKMM8YkwGsA5a2tcyuc/p+nte1+4Q2Xr8UWAqQkZGhtfzFJ9Za/rbhED9+fSunyqvq2icNjeO/b5vG6AHaq15Eujd/3Ye/h/rwnw487HwJWNR41G+MWQzkOQFeG/TrqB/lp+JZs1/EL0rPVfLI3zbzxmdH6toiDHzjitF868ox9IjSffUi0v21tT3utA5co98AbGjlJUvwbL6TCcQ7wY8x5sHa2fuasCf+sia/iO8u38ShknN1bSMTe/Ob+dOYMbK/i5WJiHSttkb4DwG3+fMDrbX5eCbmgdfEPN2KJ/5UWV3Db7N289R7uQ0W0bl95nD+7+cn0ifGb2tOiYiEhLb+1qu9xp5D/fa42doGV4LZgeKzfPuvG9iwv6SurV+vaB69ZTKfmzzYxcpERNzTVuCvwHMKPh1nZzzAGmNqvwDUbo0rEhT+ufkIi175jFNl9RPzLkpL5NfzpzK4Xy8XKxMRcVdbgb/OawGe2kl56cBVNNwa90Fr7a8DWqlIK8oqq/npG9t4cc3+uraoCMP3rh7HwktTtYiOiIS9trbHfbyZthw8p/hrvwBkAo8aY/b4c/ldkfbKPX6ab7yQw85jp+rahvXvxRN3TGf6CE3MExEB6PT9SNbaLGttBnC+H+oR8clrGw5x45MfNQj766cM5s1vX6KwFxHx4s+pyuv8eCyRVpVVVvNf/9jKX9YeqGuLiYrgJzeex+0zh2OMTuGLiHjrdOAbY3YDi/1Qi0i77C08w9deyGG716Y3qUl9+N1d6UwYHOdiZSIiwcsfI/zH8ayL/6gfjiXSqre3HuV7yzc1WB73hqlD+OUtk+mre+tFRFrU6b8ha1fKEwmkquoafvX2Lp5+P6+urUdkBD+6YSJ3zRqhU/giIm1oMfCNMXGdXWDHH8cQKTxdzrf/soFP8orq2ob178Xv75rB5GH9XKxMRCR0tDZLP8cYc0VHDmqMiTPGvAVkdqwsEY9NB0q44YmPGoT95eOSeeNbsxX2IiI+aC3wr8az7/06Y8wX2nMwY8w0Y8zTwB7gZd2XL52xPPsA85as5khpGQDGwHcyx/Lcl2cS37uHy9WJiISWFk/pO5vcjDbGPAg8boxZgWfTm3w829oWOy9NwLOlbbrzeCmQ4WyZK+KziqoafvbGNv786b66trieUfzPHdO5fNwAFysTEQldbU7ac3axe8wYk4pnSd00PHvXp+EJ/nwgG/ihswyvSIcVnCrn6y+sZ93eE3Vt4wbGsvRLMxiZ2MfFykREQlu7Z+k32tZWxO+2HCplwbJsDjun8AGunzyYx+ZO0Xa2IiKdpL9FJSj8c/MRvrd8E+cqqwHP9foHrxnPA5el6pY7ERE/UOCLq2pqLL99Zze/fWd3XVtsTBT/c+d0rtD1ehERv1Hgi2vOVVTzvZc38s/NR+vaUpL68MyXMhg9oK+LlYmIdD8KfHHF8ZNl3L8sm00HS+vaLhmTxJN3pNOvd7SLlYmIdE8KfOly2w6f5L4/rWswOe+ei0bxn9dPICqy0zs2i4hIMxT40qVW7TjGt17cwJkKz+S8yAjDT248jy9eMNLlykREujefhlPGmBpjzEvtXXlPxNuy1Xu570/ZdWEfGxPFc/fMVNiLiHQBX8+fzgcM8KwxptoJ/1sCUJd0IzU1ll/8czs/en0rNdbTNqx/L175+kVcNjbZ3eJERMKET4FvrV1hrZ1vrU0ArgFO4FmFr9oY81eN/KWxsspqvvWXDSz9oH7NpmnD43ntGxczdmCsi5WJiISXDl/Dt9ZmGWNygTxgDp7Rf4az5v4SPEvtamvcMHbiTAX3L8sme1/9MrlXTxzIb2+fTq8ekS5WJiISfnyeEm2MGWWM+aUxZjeesM8ElltrI6y1o4ExQBKQ5d9SJZQcPHGWW5/+pEHY33PRKH5/9wyFvYiIC3wa4RtjsoHpeNbUXwK80nhXPGttvjHmh0Cu36qUkLLj6Em+/Nxajp0sr2v7z+sn8NXZKVomV0TEJb6e0s8GfgLMBmYCM40xa4FnGp2+LwLm+aVCCSlr8ou4b1k2p8qqAOgRGcFvbpvK56cMcbkyEZHw5usp/fXA68D9eGbrG+AR4IQxZmrti6y1pdbaV/xWpYSEf285yhefW1sX9n1jovjjvTMV9iIiQcDXEf5iYIW19jbvRmPMSuAZ4Hx/FSah5aV1+3no1c11t90lx8bwx6/M5Lwh/dwtTEREAN8DvxhY1Ez7Qjyn+yUMLf0gj1/8c0fd45SkPiy793yGJ/R2sSoREfHma+Bn4Zm0t7dR+yhgpR/qkRBireVXb+/kd+/m1bVNGhrHH79yPkl9Y1ysTEREGvM18EuAPxhjrm7UPh/IMsb83rvRWvu1zhQnwaumxvKjv2/h+U/317Wdn5LAs1/OILandiHafgYAABWOSURBVLsTEQk2vgZ+PJ6Je2mN2tcD/Z2fWrYTdUkQq6qu4fsvb+K1jYfr2q4cP4Cn7kqnZ7TusRcRCUY+Bb619oFAFSKhoaKqhv/z1w38a8vRurabpg3hV/OmEq2tbUVEglaHltY1xlwJpAOJwNvW2nd9eG88ntX5AGZaaxc57XPxXDJIt9Y+1pG6JLDKKqv5+gs5rNpxvK7trlkj+NlNk4iI0II6IiLBrCNL676NZ/Le7XjW0H/HWXynveYDCdbaFc7xFjhhj7U2CygxxmS2dgDpemcrqrjvT9kNwv6+2Sn8/GaFvYhIKPAp8L0m5fW31mZYazOABCDCGPNUe45hrV1qrV3qPEzF8+VhJp7lenH+TPelLgms0+VV3PO/6/got7Cu7ZtXjOaR6ydoqVwRkRDh6wh/PrDAWlta22CtLXHab2vxXc0wxqQCxdbafDyTAb0l+liXBMjp8irueW4ta/cU17V9/+qxfP+acQp7EZEQ4mvgG5qffd+R5dTmWmsXOr+X4DlT0PIHe079ZxtjsgsKCjrwceKrU2WVfPm5tQ12vHvkugl888oxLlYlIiId4WvgPwMsNcbE1jYYY+Kc9uXtPYgxZm7txDznev066kf5qTSziI9zKSDDWpuRnJzsY9niq9qwX+8V9j/6/ETuvzTVxapERKSjfAp8Z0b9STwT63YbY3YDJ4Ci9i6y4wT8YmPMemPMeue4K4DU2sl6zuQ9cUlt2OfsL6lr+/ENE7l3doqLVYmISGf4fFuetXaeMSYduMppyrHWvuPD+7NounAPuhUvOJwur2oS9j+5YSL3XKywFxEJZT4FvjFmmrV2o7U2B8gJUE3ikrMVVdz7x3UKexGRbsjXa/h/MMZ8ISCViKvKKqu5f1l2g9n4P1bYi4h0G74G/qPAY96T9iT0lVdV88Dz6/k4t6iu7eHrxvMVhb2ISLfh6zX8FDy35u01xmRRv1gOANbah/xVmHSNyuoavvniBt7bWX+r4/evHsuCS5tMsxARkRDma+B7r4jXH5jh9Zx2xwsx1TWW7y3fxMptx+ravn3laN1nLyLSDfm6W978QBUiXctay49e38LfN9VvcbvwslS+M2esi1WJiEig+LqWflxL7caYUf4oSALPWsuj/97BC2v217XdfcEIfnjteC2XKyLSTfk6ae9EC+1zgCWdrEW6yFPv5bHk/frpFzdPG8JPb5yksBcR6cY6spZ+c/KBjE7WIl3gz5/u4/G3dtY9njNxII/Pm6otbkVEurl2XcM3xuTimZRnneV0vSXgWQc/v8kbJai88dlhfvT6lrrHF6Ul8sQd04mO9PV7n4iIhJr2TtpbhGd0vxxobgncfF+W15Wu93FuId95aSPWuZdi6vB4ln4pg57Rke4WJiIiXaJdgW+tfQXAGJNlrX0msCWJv20+WMqCZdlUVnvSPjW5D/97z0z6xvi8lYKIiIQoX3fLuzpQhUhg7Ck8wz3/u5YzFdUADIrryZ+/OouEPj1crkxERLqSr7flXelsi1vd3E+gipSOOX6qjC89t4aiMxUA9OsVzbKvns/Q+F4uVyYiIl3N13O6S/FMzvshUNLGa8VFZ8o9O98dKD4HQM/oCJ67J4OxA7UNgohIOPI18BOATGvt3gDUIn5SVV3DN17MYcuhkwBEGPjdnenMGJngcmUiIuIWX+/HWg5MD0Qh4h/WWv7ztS0NNsP5+c2TuWrCQBerEhERt/k6wi8BVhhjcoDsxk9aa7/ml6qkw55Ylctf1x2oe/ytK0dz56wRLlYkIiLBwNfATwVq77dvvH+qdstz2SvrD/KblbvqHt+SPpTvajMcERFBu+V1G6vzivjhq5/VPZ49OolHb5mi9fFFRATw/Rq+BKG8gtM88Pz6uoV1xg+K5fd3p9MjSv96RUTEo9VEMMa81XhLXGPMlc28LkX34buj+EwF9/5xHaXnKgFIjo3h2XtmEtsz2uXKREQkmLQ1BJyD51Y8bytbeK3OHXex8qpqFv45m31FZwHPvfbPfjlDC+uIiEgTHTnn21Kwa9JeF7LWsmjFZ6zbewIAY+C3t09nyrB4lysTEZFg1JHAV7AHgd+9m8trGw/XPX74cxO45rxBLlYkIiLBTLO6QtC/txzhV2/X3353x/kjuO+SFBcrEhGRYNeewNeIPohsOVTKd17aVPf4wtREfnrTebr9TkREWtWe+/DzG4WJ0Yx8dxw/Vcb9y7I5V+np/pGJvXnqrnSiI3WiRkREWtdW4C/qkiqkTWWV1SxYtp4jpWUAxMZE8eyXM+ivfe1FRKQdWg18a+3jXVWItMxay8OvbmbjAc+OxBEGnrhzOqMHaKtbERFpH50LDgHPfrSHVzccqnv8yPUTuXzcABcrEhGRUKPAD3If7i7gF//cXvd43oxh3HvxKPcKEhGRkKTAD2L7is7wzRc3UOPcJzF9RDw//8IkzcgXERGfKfCD1OnyKu5fll23Rv6A2BievnsGMVGRLlcmIiKhSIEfhGpqLN9bvpFdx04D0CMygiVfnMHAuJ4uVyYiIqFKgR+Ennovl7e2Hqt7/ItbJjN9RH8XKxIRkVDnSuAbYzKNMSsbtc112h90o6Zg8e7O4/x6Zf2yufdcNIq5M4a5WJGIiHQHrgS+tTbL+7ExZq5Xe4kxJtONuty2r+gM/+cvG7DOJL1ZKQk8cv0Ed4sSEZFuIVhO6c8E8p3f84F0F2txxdmKKhb+eT0ny6oAGBTXkyfv1LK5IiLiH8GSJo03cU9s/AJjzAJjTLYxJrugoKCLyuoa1loeXPEZO46eAjyT9J7+4gySY2NcrkxERLqLYAn8EiChtRdYa5daazOstRnJycldVFbXePajPbzx2ZG6xz+7+TymDW/8HUhERKTjgiXw11E/yk8FVrby2m7l0/wifvmvHXWP75w1gttmjnCxIhER6Y7cmqU/F8jwmqy3AkitnazXeFJfd3W0tIxvvphDtbOU3rTh8fz4hokuVyUiIt1RW9vjBoQT8CsatT3mRi1uqaiq4esvrKfwdAUASX178Pu707WSnoiIBESwnNIPOz9/cxs5+z3b3UZGGJ64I53B/Xq5XJWIiHRXCnwXvJpzkGWr99U9XnTtOC5Ma3JjgoiIiN8o8LvYtsMnefhvm+seXzd5EPdfkupiRSIiEg4U+F2o9GwlDzy/nrLKGgDSkvvw2Nyp2u5WREQCToHfRWpqLN9dvpH9xWcB6NMjkiVfnEHfGFfmTYqISJhR4HeRp97L5Z0dx+sePz5vKqMHxLpYkYiIhBMFfhf4YFdBgx3wFlyaynWTB7tYkYiIhBsFfoAdPHGWb/+14Q54D14zzt2iREQk7CjwA6isspoHnl9PydlKAAbGxfDknelEaQc8ERHpYkqeALHW8sjftrDl0EkAoiIMT92Vrh3wRETEFQr8AHl+zX5eyTlY9/jHN0xkxshWNwQUEREJGAV+AKzfV8xP/7G17vGt6cO4+4KRLlYkIiLhToHvZ8dPlfG153OorPbM0ps0NI7/7wuTtLiOiIi4SoHvRxVVNXzjhRyOnyoHoH/vaJ6+ewY9o7UDnoiIuEuB7yfWWn78962s23sCgAgD/3PHdIb17+1yZSIiIgp8v3n+0338Ze3+uscPXjueS8Yku1iRiIhIPQW+H6zOK+K//rGt7vHN04aw8FLtgCciIsFDgd9JB4rP8vUX1lNV45mkN2VYPx69dYom6YmISFBR4HfCmfIq7l+WzQlnJb2kvjEs+aIm6YmISPBR4HdQVXUN33wxhx1HTwHQIzKCJV9MZ3C/Xi5XJiIi0pQCvwNqZ+S/u7Ogru3nN0/SSnoiIhK0FPgdsOSDfF5YUz8j/+uXpzF/5nAXKxIREWmdAt9H/9h0mEf/taPu8Y1Th/D9q7XdrYiIBDcFvg/W7inme8s31T0+PyWBx+dNISJCM/JFRCS4KfDbaeOBEr76x3VUVNcAkJrch6VfnEFMlGbki4hI8FPgt8OWQ6V86dk1nCqvAiCpbw/+9JXzie/dw+XKRERE2keB34Zth09y97NrOFnmCfv+vaN5/r5ZDE/QGvkiIhI6FPit2HXsFHc/u4YSZ2Gdfr08YT9+UJzLlYmIiPhGgd+CTQdKuPOZTyk+UwFAbM8onv/qLM4b0s/lykRERHwX5XYBweiNzw7zveWbKK/yTNDrGxPFsnvPZ/Iwhb2IiIQmBb4Xay1Prsrl1yt31bX16xXNc/dkMH1EfxcrExER6RwFvqOsspofvvIZr208XNeWmtSHZ++ZSUpSHxcrExER6TwFPvDh7gJ+9PpW9hSeqWu7eHQiT905g369o12sTERExD/COvCPlpbxsze38eZnRxq03zlrBP9143lER2pOo4iIdA9hGfhHSs+xIvsgT7+fx5mK6rr22J5RPHzdBG6fORxjtFyuiIh0H0ET+MaYuUAJkG6tfczfxz9ZVsm/txzlbzmH+HRPEdY2fP6W6UN56LoJJMfG+PujRUREXBcUge+EPdbaLGNMqjEm01qb1dLrK6stR0rPUWOhpsZiLZRVVXO2opqzFVWcq6im6HQFeYWnyTt+hvzC0+wvOktVjW1yrNED+vKzmyZxYVpiAP8JRURE3BUUgQ/MBF5yfs8H0oEWA3/H0ZNc+MtVHf6wCAMXj07i5mlDuWHqEHpE6Vq9iIh0b8ES+PGNHjcZbhtjFgALAHoMGt2hD5k4OI4vTB/KjdOGMDCuZ4eOISIiEoqCJfBLgITWXmCtXQosBegzdKwdFNeTCAPGGIyBmKgI+sRE0Ss6kt49IontGU1KUh9Sk/uQltyX1OQ+9O4RLP+4IiIiXStYEnAd9aP8VGBlay+eMDiOTx++KuBFiYiIdBdBcfHaWrsCSDXGZDqPW7x+LyIiIr4LlhE+gbgVT0RERDyCYoQvIiIigaXAFxERCQMKfBERkTCgwBcREQkDCnwREZEwoMAXEREJAwp8ERGRMKDAFxERCQPGNt4YPgQYY04BO92uIwwkAYVuF9HNqY8DT30ceOrjrjHOWhvb0TcHzUp7Ptpprc1wu4juzhiTrX4OLPVx4KmPA0993DWMMdmdeb9O6YuIiIQBBb6IiEgYCNXAX+p2AWFC/Rx46uPAUx8Hnvq4a3Sqn0Ny0p6IiIj4JlRH+CIiIuKDkAt8Y8xcY0ymMeZBt2sJdcaYeKc/5xpjFnu1N+lj9XvnqY8DyxiTXvvfs1eb+tmPvPpuQTNt6uNOcPprZaO2dvVte/s7pAK/9n9ka20WUGKMyXS5pFA3H0iw1q4AMMYsaK6P1e+d5/RZqvO7+jgwHnL+W041xqSqn/3L6at8p+/ya79ggfrYH5z+qtPevvWlv0Mq8IGZQL7zez6Q7mItIc9au9RaWzsJJBXIovk+Vr93gjEmlfr+A/Wx3zkjzpXGmFRr7WPW2nzUz/6WDbxsjEkHUq21OaiPA6m9fdvu/g61wI9v9DjRlSq6GSeQip2/JJvrY/V756Q6fVtLfex/ac5PsTFmiTEmHvWzX1lrS4AlwMt4+hrUx4HU3r5td3+HWuCXAAluF9ENzbXWLnR+b66P1e8dZIzJbHyqDvVxoOQ5obQeWID62a+cU8dZ1to0r8fq48Bpb9+2u79DbWndddR/m0kFVrbyWmkHY8xca+1jzu+ZNN/H8c20SfsUO/0aj+facjrq40BYR/1fevF4/hL0PmOlfu681Nr5PsAv8cwB0n/LgdPevm13f4fUCN9rQk6m87jxyEl84PTjYmPMemPMemi+j9XvHWetzXH6KwHnf0r1sf85/Rfv1X9L1c9+t9SZ2JsJzFcf+5dzxiTDaxJeu/rWl/7WwjsiIiJhIKRG+CIiItIxCnwREZEwoMAXEREJAwp8ERGRMKDAF5GQ5Cyfm+cssuOP4630XodfpLtR4It0knOr0ol2/Cxo+2jig5XAQmexnTrOF4HFxhjr3HK6uJnnTzhfFrw3G5kHPOOsPCnS7ei2PJFOckaY3itdpeNZfnQekOPVXtw4nKRjnKC+zVo7o4Xn44ETwAxnzXfv59KBzNoFpxo9txhIt9bOCUDZIq5S4Iv4mRMo62kmbLoD57T34tolVl2qIQ9Y5LXyW+Pn5wIvW2tNM+35Lf178fqi0F9fzqS70Sl9EQkpzin31JbC3jEHz+6P3u9bgGct+Ba/hDkhn4Nn2ViRbkWBL9LFnN3caq8hL/Bqf9m59uz9fKbzk+dck365mWPVvievubkCbXzeg8aYuc617nSnvfaxdd4z1+s9K/Fcrkh1nre1k+acSW9LvF6baYyxbX1eazW2IJOG2w239JqVzrHjjTEPOkvBtmfUno3nC4NIt6LAF+lCTmCmAjOAhcASr0li8cCDeIJqBp5QexlYhCeA5gFzG80kT8WzM9xK6ke1dcdsx+ctBBYDv/Qa+SYA9wP9nedern2Pc217IZ7T4sb5ae+p72Y/r40am5NGK4HvfAFJBbKcLxXvALe1s0aAPOf9It2KAl+ki9ROFsMzszzf2eRiKZ6Qq5VjrV1hrc3Hs/d4PJ7r5fnOKex8mobR8tr3WGvn4dkpbmE7Py8Bz1yDutPjzkg4x1pbYq1d6hwv00/d0ODz2lljY7W74bWkttbafloEpPsw+74EBb50Q6G2Pa5IKMtw/swzpsFcMu9r0dlev5e00JbYxudk4Qms9nxeVnMjdOe0+hznON7bb3ZW489rT42NpdL6Kf2ZzvN1n2WMyccT/K19kahVjP/+eUWChgJfpGvl+zq7vZOzxdv6vCbBaTxbJRfjOfWejeeOA39pLqh97ZO2+iMTWNGo3xbjOWPSnsBvz2eIhByd0hfpOll4JrsFevSYCazryOc5p9jTgXnOXtstBV9CC+3e2vO5HemT/DY+Px1nwp6X5VB35qItCXi+8Ih0Kwp8kS7iXJdfAbzjrPYW76zS92Bb723DfGdGfKozAS4eWNrBz6sdgS+ofT1Nr2fnA/HGmHRnxn1tWJcAGc77UoGH2iq8gzUWNVMT4LkzwDlug1vynC8uS/Gc1m9Lq5MCRUKVAl+kCzmT6rLwnCbfg2fmfVarb2pbFp5T1eupnxRX0pHPc973GJ5T4HvwhF8OXqe4nTDNxzP7fSH1o+0leIJ4D/Wn0NsMzg70SQ6eUXwDzip5i2t/9z5r4HwRyMRzNuHlNs4opNNwhUSRbkEr7YmEMGdEn2+tbe+16W7Bub8/ICsZGmNOAFd1x1USJbxphC8ioaitW/c6pHaNA4W9dEcKfBEJRYvxzF3w9wTIh/AsOiTS7SjwRSTkOJP9FuFZidAvnImCtQsciXQ7uoYvIiHLOQXf2u2DPh1LYS/dmQJfREQkDOiUvoiISBhQ4IuIiIQBBb6IiEgYUOCLiIiEAQW+iIhIGFDgi4iIhIH/H0dtyVhwEV5rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#entropy_unit = 'eV/K'\n",
    "entropy_unit = 'J/K/mol'\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "entropy = uc.get_in_units(thermal['entropy'], entropy_unit)\n",
    "plt.plot(temperature, entropy, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Entropy (${entropy_unit}$)', size='xx-large')\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "heat_capacity_v = uc.get_in_units(thermal['heat_capacity_v'], entropy_unit)\n",
    "heat_capacity_p_numerical = uc.get_in_units(thermal['heat_capacity_p_numerical'], entropy_unit)\n",
    "heat_capacity_p_polyfit = uc.get_in_units(thermal['heat_capacity_p_polyfit'], entropy_unit)\n",
    "\n",
    "plt.plot(temperature, heat_capacity_v, '-', lw=3, label='Cv')\n",
    "plt.plot(temperature, heat_capacity_p_numerical, '-', lw=3, label='Cp (numerical)')\n",
    "plt.plot(temperature, heat_capacity_p_polyfit, '-', lw=3, label='Cp (polyfit)')\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Heat capacity (${entropy_unit}$)', size='xx-large')\n",
    "plt.legend(loc=4, fontsize='xx-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Volume versus temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "volume_unit = 'Å^3'\n",
    "#volume_unit = 'nm^3'\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "volume = uc.get_in_units(thermal['volume'], volume_unit)\n",
    "plt.plot(temperature, volume, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Volume (${volume_unit}$)', size='xx-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thermal expansion versus temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,5))\n",
    "expansion = thermal['thermal_expansion']\n",
    "plt.plot(temperature, expansion, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Thermal expansion', size='xx-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grüneisen parameter versus temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,5))\n",
    "gruneisen = thermal['gruneisen']\n",
    "plt.plot(temperature, gruneisen, '-', lw=3)\n",
    "plt.xlabel('Temperature ($K$)', size='xx-large')\n",
    "plt.xlim(0, 1000)\n",
    "plt.ylabel(f'Grüneisen parameter', size='xx-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "qha = results_dict['qha_object']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 25,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qha.plot_bulk_modulus()\n",
    "plt.xlabel('Volume ($Å^3$)', size='large')\n",
    "plt.ylabel('Energy ($eV$)', size='large')\n",
    "plt.savefig('test.png', dpi=400, bbox_inches='tight')\n",
    "plt.close()\n",
    "Image(\"test.png\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "  "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
